It’s Not Only What you Say, It’s Also How You Say It: The Strategic Use of Campaign Sentiment

Abstract

What explains the type of electoral campaign run by political parties? We provide a new perspective on campaigns by focusing on the strategic use of emotive language. We argue that the level of positive sentiment parties adopt in their campaigns depends on their incumbency status, their policy position, and objective economic conditions. We test these claims with a novel dataset that captures the emotive language used in over 400 party manifestos across eight European countries. As predicted, we find that incumbent parties, particularly incumbent prime ministerial parties, use more positive sentiment than opposition parties. We find that ideologically moderate parties employ higher levels of positive sentiment than extremist parties. And we find that all parties exhibit lower levels of positive sentiment when the economy is performing poorly but that this negative effect is weaker for incumbents. Our analysis has important implications for research on campaign strategies and retrospective economic voting.

Full text

It’s Not Only What you Say, It’s Also How You Say It:
The Strategic Use of Campaign Sentiment∗
CHARLES CRABTREE†
University of Michigan
MATT GOLDER‡
Pennsylvania State University
THOMAS GSCHWEND§
University of Mannheim
INDRIÐI H. INDRIÐASON¶
University of California, Riverside
ABSTRACT
What explains the type of electoral campaign run by political parties? We provide a new perspective on cam-
paigns by focusing on the strategic use of emotive language. We argue that the level of positive sentiment
parties adopt in their campaigns depends on their incumbency status, their policy position, and objective
economic conditions. We test these claims with a novel dataset that captures the emotive language used in
over 400 party manifestos across eight European countries. As predicted, we find that incumbent parties,
particularly incumbent prime ministerial parties, use more positive sentiment than opposition parties. We
find that ideologically moderate parties employ higher levels of positive sentiment than extremist parties.
And we find that all parties exhibit lower levels of positive sentiment when the economy is performing
poorly but that this negative effect is weaker for incumbents. Our analysis has important implications for
research on campaign strategies and retrospective economic voting.
∗NOTE: We thank James Adams, Nicole Baerg, Jason Eichorst, Sona Golder, Michael Lewis-Beck, Thomas Meyer, Jonathan
Nagler, Simone Paolo Ponzetto, Rüdiger Schmitt-Beck, Laron Williams, participants at the 2015 Making Electoral Democracy
Work Workshop at Sciences Po (Paris), the 2016 Making Electoral Democracy Work Workshop at the University of Montreal, the
2016 Annual Meeting of the Midwest Political Science Association, the 2016 Annual Meeting of the American Political Science
Association, and the audience at the University of Pittsburgh for their helpful comments. We acknowledge financial support for this
research from the Social Sciences and Humanities Research Council of Canada. All data and computer code necessary to replicate
the results in this analysis will be made publicly available on our webpages on publication. Stata 14 was the statistical package
used in this study.
†Ph.D. Candidate, Department of Political Science, University of Michigan, 505 South State Street, Ann Arbor, MI 48109.
(ccrabtr@umich.edu).
‡Corresponding Author: Professor, Department of Political Science, Pennsylvania State University, 306 Pond Lab, University
Park, PA 16802 (mgolder@psu.edu).
§Professor, Department of Political Science, University of Mannheim, A 5, 6, D-68131, Mannheim, Germany
(gschwend@uni-mannheim.de).
¶Professor, Department of Political Science, 900 University Avenue, University of California, Riverside, CA 92521
(indridi.indridason@ucr.edu).

What explains the type of electoral campaign run by political parties? To a large extent, scholars
have conceptualized electoral campaigns along two primary dimensions. The first dimension captures cam-
paign content – whether parties compete on policy or valence (Downs,1957;Ansolabehere and Snyder,
2000;Schofield,2003;Adams,2001;Adams, Merrill and Grofman,2005;Adams, Scheiner and Kawasumi,
2016). The second dimension captures campaign focus – whether parties adopt campaign messages that
focus on themselves or their opponents (Skaperdas and Grofman,1995;Lau and Pomper,2002;Geer,2006;
Elmelund-Præstekær,2008,2010;Hansen and Pedersen,2008). One aspect of campaigns that is ignored
in this two-dimensional framework is campaign sentiment, which refers to the emotive content of cam-
paigns. Whereas campaign content and campaign focus address what parties say and who they say it about,
campaign sentiment addresses how they say it.
Scholars have recently begun to examine how the emotive content of campaign or issue advocacy
messages affects voter behavior (Marcus, Neuman and MacKuen,2000;Brader,2006;Huddy and Gun-
nthorsdottir,2000;Roseman, Abelson and Ewing,1986;Weber, Searles and Ridout,2011;Utych,2018).
The common thread in this literature is that voters are not merely influenced by the substantive content of
campaigns but also by their emotive content. Studies have repeatedly shown that electoral campaigns can
be manipulated to trigger emotional responses that, in turn, produce predictable changes in voter behavior.
This raises a natural question. If campaign sentiment influences voter behavior, then political actors should
be strategic about its use. Are they? With the exception of Ridout and Searles (2011), who focus on the
two-party context in the United States,1we know of no research that explicitly looks at the strategic use of
emotion in electoral campaigns.
In this article, we examine the strategic use of emotive language in European election campaigns.
Studies that look at emotion in campaigns have typically focused on the use of images and music (Huddy and
Gunnthorsdottir,2000;Brader,2006). However, language can also engender different types of sentiment,
such as fear, anxiety, sadness, or optimism (Pennebaker,1993;Pennebaker and Francis,1996). We build
on a long tradition that emphasizes how language can shape how individuals perceive the world around
them (Edelman,1964,1977;Hipt,1990;Hart, Childers and Lind,2013). The importance of language is
emphasized by Edelman (1985, 10), who argues that “political language is political reality.” Academic
and non-academic observers have recently pointed to Donald Trump’s election campaign to highlight the
significance that word choice plays in politics (Healy and Habermandec,2015;Lakoff,2016). Of particular
1Ridout and Searles (2011) examine emotional appeals in 26 U.S. Senate races in 2004.
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interest to us is whether parties adopt language that conveys positive or negative sentiment. Campaign
messages that include positive emotive language evoke optimism and encourage people to adopt a positive
frame when evaluating the current state of the world. In contrast, campaign messages that include negative
emotive language have the opposite effect.
Our theory is situated in the retrospective voting literature. Models of retrospective voting assume
that individuals base their vote choice on the state of the world at election time, something that is usually
attributed to incumbent performance in office. Typically, the state of the world is understood in economic
terms (Norpoth, Lewis-Beck and Lafay,1991;Lewis-Beck and Stegmaier,2000;van der Brug, van der Eijk
and Franklin,2007;Nadeau, Lewis-Beck and Éric Bélanger,2013). The basic intuition is that people will
vote for the incumbent when economic performance is above some threshold but switch to the opposition
when this is not the case. The ability of individuals to vote retrospectively depends on a variety of contextual
factors such as the ease with which they can attribute responsibility for economic performance to individual
incumbent parties (Powell and Whitten,1993;Duch and Stevenson,2008). The core insight, though, is that
vote choice is determined by how individuals perceive the state of the world.
Extant research largely assumes voter perceptions are related to objective economic reality. In effect,
individuals are expected to have a more positive view of the world and, thus, evaluate the incumbent more
favorably when, say, the unemployment rate is low. What tends to be overlooked, though, is that political
elites can exert agency and shape retrospective voting by using their campaign messages to frame how
individuals evaluate economic reality. Williams, Seki and Whitten (2016) have recently shown that parties
strategically use campaign messages to emphasize or deemphasize economic issues. By altering the salience
of economic issues, parties can influence how voters weigh economic conditions in their voting calculus.
In this particular account, parties do not seek to change how voters perceive objective economic reality but
rather how much they care about it.
We argue that a complementary strategy parties can adopt involves using emotive language to alter
how individuals perceive economic conditions. Objective reality can be understood very differently depend-
ing on how it is framed. For example, a message that “the economic outlook is positive, with employment
increasing by 150,000” provides a much more positive frame for viewing the world than a message that
“employment increased by only 150,000.” Such differences in the strategic use of positive and negative
emotive language, can substantially influence how individuals perceive the world (Chong and Druckman,
2007;Zaller,1992;Utych,2018) and, hence, how they vote. Our theoretical account provides an explana-
2

tion for why supporters of different parties often hold varying perceptions of objective economic conditions
(MacKuen, Erikson and Stimson,1989;Duch, Palmer and Anderson,2000;Anderson,2007;Enns, Kellstedt
and McAvoy,2012).
Our retrospective voting framework suggests that the level of positive campaign sentiment exhibited
by political parties should depend on their incumbency status, their policy position, and objective economic
conditions. Incumbent parties, particularly prime ministerial parties, should exhibit greater positive senti-
ment in their campaigns than opposition parties. This is because incumbents are expected to gain support
when voters have a more positive view of the world. The campaigns of extremist parties should be char-
acterized by less positive sentiment than those of more moderate parties. This is because extremist parties
are expected to gain support when the world is viewed in a particularly negative light. The language that
parties adopt cannot diverge too far from reality, though, otherwise voters will become suspicious. This sug-
gests that the campaign sentiment of all political parties will be tied to some extent to objective economic
conditions. Thus, parties should exhibit greater positive sentiment when economic conditions are good.
This increase in positive sentiment, though, should be greater for incumbent parties, as they are the prime
beneficiaries of improved economic conditions.
We test our claims using a novel dataset we constructed of the emotive language used in over 400
party manifestos across eight European countries from 1980 to 2012. Party manifestos are obviously only
one type of campaign message. However, they are of particular relevance as they contain the campaign mes-
sages parties have strategically chosen to present to voters, a look that is not filtered through the lens of the
media. Moreover, party manifestos outline the overarching campaign strategy of parties in a way that, say,
party press releases, which emerge irregularly throughout the campaign in response to ad hoc developments,
might not. Historically, scholars have used manifestos to examine issue salience and party positions (Budge
et al.,2001). Our focus on the strategic use of emotion in manifestos, thus, extends the use of manifestos
in a completely new direction. Our empirical results strongly support our theoretical expectations and have
important implications for the literatures on both campaign strategies and retrospective voting.
Theory
Existing research largely focuses on two dimensions of election campaigns. The first dimension, campaign
content, has to do with whether parties compete on policy or valence. Early models of electoral competition
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were purely spatial and focused on the policy positions adopted by each party (Downs,1957;Wittman,
1973). More recent models incorporate non-spatial valence factors such as party competence, integrity, and
experience (Ansolabehere and Snyder,2000;Schofield,2003;Adams,2001;Adams, Merrill and Grofman,
2005). The development of these newer models can be traced to a recognition that individuals often have
little incentive to gather the information needed to evaluate parties in terms of their policies (Popkin,1991;
Lupia and McCubbins,1998) and that voters often use information short-cuts and heuristics (Sniderman,
Brody and Tetlock,1991;Marcus, Neuman and MacKuen,2000).
The second dimension, campaign focus, concerns whether parties focus their campaign messages on
themselves or their opponents (Skaperdas and Grofman,1995;Lau and Pomper,2002;Elmelund-Præstekær,
2008,2010;Hansen and Pedersen,2008;Lau and Rovner,2009). This dimension is sometimes referred to
as campaign tone, with messages that focus on one’s own party considered positive and those that focus on
other parties considered negative (Geer,2006). In our opinion, this terminology is confusing as it mixes up
the ‘focus’ or target of campaign messages with the ‘tone’ or sentiment of campaign messages, two things
that are conceptually and empirically distinct (Ridout and Franz,2011).
Although scholars often examine these two dimensions in isolation, they can be put together to ob-
tain four ‘pure’ types of electoral campaigns, as is shown in Figure 1. A spatial campaign is one in which
parties appeal to voters by highlighting their own policies. This is the type of campaign captured in tra-
Figure 1: A Two-Dimensional Conceptualization of Electoral Campaigns
Valence Policy
Campaign Content
Own Party Other Party
Campaign Focus
‘Spatial’
Campaign
‘Comparative’
Campaign
‘Valence’
Campaign
‘Attack’
Campaign
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ditional spatial models of electoral competition. A comparative campaign is one in which parties seek to
emphasize the inferiority of their opponent’s policies. A valence campaign is one in which parties appeal
to voters by emphasizing their own valence characteristics. In contrast, an attack campaign is one in which
parties point out the poor valence qualities of their opponents. This last type of campaign is often what the
media have in mind when they talk about ‘dirty politics’ and ‘negative campaigning’. This two dimensional
conceptualization of electoral campaigns focuses on what parties say and who they say it about.
A key aspect of electoral campaigns that is overlooked in this two-dimensional framework is cam-
paign sentiment. Campaign sentiment refers to the emotive content of campaigns and has to do with how
parties convey their substantive ideas. It is widely recognized that politicians make emotional appeals to the
public (Hart, Childers and Lind,2013), and recent research indicates that these appeals can have a significant
effect on voter behavior (Marcus,2000;Brader and Marcus,2013). For example, Brader (2005,2006) finds
that campaigns evoking fear cause individuals to reconsider their political choices, whereas those evoking
enthusiasm cause them to stick with their pre-existing preferences. Similarly, Utych (2018) finds that politi-
cal candidates are evaluated more negatively when they are described using negative emotive language than
when they are described using neutral emotive language. As a whole, this research is consistent with the
idea that individuals process information differently depending on their emotional mood (Schwarz,2000).
Empirically, the emotive content of campaigns does not correlate meaningfully with the two dimen-
sions shown in Figure 1. It is known, for example, that campaigns that focus on one’s own party do not
always contain positive emotive content, and those that focus on other parties do not always contain nega-
tive emotive content (Ridout and Searles,2011). In their analysis of campaign messages, Ridout and Franz
(2011, 101) conclude that “[o]ne thing is clear. [Campaign focus] and emotional appeals are not one and the
same.” Studies also reveal significant variation in the use of emotion across the campaign content dimen-
sion (Ridout and Franz,2011, 94-95). Importantly, Utych (2018) finds that altering the emotive nature of
the language used to describe political candidates influences how these candidates are evaluated even after
controlling for the substantive content and focus of the candidate descriptions. Thus, both conceptually and
empirically, campaign sentiment represents a third and distinct dimension of electoral campaigns.
If campaigns can be manipulated to elicit particular emotions and thereby influence voter behavior
in predictable ways, as the existing literature suggests, then we should expect political actors to be strategic
in their use of emotion. To date, there has been no research on whether and how these actors strategically
employ emotion in multiparty elections. In this article, we argue that parties strategically use emotion in
5

their campaign messages to frame the state of the world in either a positive or negative light.
The incentive to frame the state of the world in a particular way can be tied to the logic underpinning
models of retrospective voting. These models assume that an individual’s vote choice depends on how they
view the world. The state of the world is understood to be determined, at least partially, by the incumbent’s
performance in office. Individuals reward the incumbent when they perceive the state of the world to be
good, but punish her when they perceive it to be poor. In most cases, the state of the world is understood in
terms of the economy.
If vote choice is influenced by how we perceive the state of the world, then parties have incentives
to shape those perceptions through their campaigns. One way parties can do this is through the substantive
content of their campaign messages. For example, a party might highlight how its own policies and valence
characteristics can change the world for the better, or it might emphasize how those of its competitors would
make things worse. A complementary way to influence how voters perceive the world, though, is through
the emotive content of their campaigns. The use of positive campaign sentiment can evoke optimism and
encourage voters to adopt a positive frame when evaluating the state of the world. In contrast, the use of
negative campaign sentiment can evoke pessimism and encourage voters to adopt a negative frame when
assessing the world around them. In effect, parties can influence perceptions of the world and, hence, vote
choice not only through the substantive content of their campaign messages but also through the emotive
content of their campaigns. Indeed, it seems plausible that voters are better at assessing the overall sentiment
in campaign messages than the often detailed substantive positions that are staked out in these messages.2
In this regard, incumbent parties should exhibit higher levels of positive sentiment in their campaign
messages than opposition parties. This is because incumbents, who are perceived as responsible for the
current state of the world, can expect to gain support when voters view things in a more positive light.
Incumbent Party Hypothesis: Incumbent parties use higher levels of positive sentiment in
their campaign messages than opposition parties.
When there is only one party in government, it is clear who voters should hold responsible. It is
much less clear, though, who they should hold responsible when there is a coalition government (Powell
and Whitten,1993;Duch, Przepiorka and Stevenson,2015). That the prime minister is the most visible
member of the government and is widely recognized as the agenda setter (Norpoth and Gschwend,2010;
2Importantly, research has shown that emotional responses to the economic state of the world have a particularly strong impact
on how individuals evaluate political actors (Conover and Feldman,1986).
6

Duch and Stevenson,2013) suggests that voters will hold the prime ministerial party more responsible than
its coalition partners. Indeed, empirical evidence consistently shows that the economic vote for the prime
ministerial party is large compared to that of other governmental parties (Duch and Stevenson,2008;Debus,
Stegmaier and Tosun,2014). A consequence is that prime ministerial parties have a particularly strong
incentive to portray the world in a positive light and should therefore exhibit even higher levels of positive
campaign sentiment than their coalition partners.3
Prime Ministerial Party Hypothesis: Prime ministerial parties use higher levels of positive
sentiment in their campaign messages than their coalition partners.
The level of positive sentiment parties exhibit in their campaigns should also depend on their policy
position. Even controlling for their incumbency status, we would expect ideologically extreme parties to
exhibit less positive sentiment than ideologically moderate parties. This is because voters are more likely
to reject moderate parties and turn to more extreme parties when they perceive the state of the world to be
particularly bad. Radical parties in Europe, for example, propose ‘root and branch’ reform of the political
and economic system and many adopt populist rhetoric that holds all moderate parties responsible for soci-
ety’s ills (Mudde,2007;Golder,2016). These parties do not just want voters to punish the incumbent, they
want voters to abandon the mainstream parties altogether. This is most likely to occur when the current state
of affairs is considered particularly problematic. This reasoning fits with media accounts linking the recent
success of left- and right-wing radical parties to Europe’s economic crisis.
Extreme Ideology Hypothesis: Ideologically extreme parties use lower levels of positive sen-
timent in their campaign messages than ideologically moderate parties.
The level of positive sentiment parties exhibit in their campaigns should also vary with objective
measures of the state of the world. While parties will try to use the emotive content of their campaigns to
get voters to see the world through a particular frame, the extent to which they can do this is constrained by
economic reality (Nadeau, Lewis-Beck and Éric Bélanger,2013;Lewis-Beck, Martini and Kiewiet,2013).
If the campaign sentiment parties adopt is too positive when times are bad or too negative when times are
good, then voters may get suspicious and punish them for their lack of credibility. Thus, we should expect
the level of positive sentiment exhibited by all parties to vary in line with objective measures of the economy.
3Some scholars suggest that voters may also attribute responsibility for the state of the world to the finance ministry party
(Williams, Seki and Whitten,2016). However, the empirical support for this claim is rather mixed (Duch and Stevenson,2008;
Debus, Stegmaier and Tosun,2014). In our own analyses in Online Appendix A, we find little evidence that parties controlling the
finance ministry use higher levels of positive campaign sentiment than their coalition partners.
7

Economic Performance Hypothesis: Campaign messages will exhibit lower levels of positive
sentiment when the economy is performing poorly than when it is performing well.
There are reasons to believe that economic conditions and a party’s incumbency status interact to
determine levels of positive campaign sentiment. The negative effect of poor economic performance on
positive campaign sentiment should differ depending on whether a party is in government or not. This is
because incumbent parties have an incentive to downplay the poor performance of the economy, whereas
opposition parties have an incentive to exaggerate it.
Conditional Economic Performance Hypothesis: Campaign messages will exhibit lower lev-
els of positive sentiment when the economy is performing poorly than when it is performing
well. This negative effect of poor economic performance is weaker for incumbent parties than
for opposition parties.
All conditional claims are symmetric (Berry, Golder and Milton,2012), and the Conditional Eco-
nomic Performance Hypothesis logically implies that the effect of a party’s incumbency status on positive
campaign sentiment depends on how well the economy is performing. Incumbent parties should always use
more positive sentiment in their campaigns irrespective of the state of the economy. However, the positive
effect of incumbency should be greater when the economy is performing poorly. This is because opposi-
tion parties will want to use particularly negative emotive language relative to incumbent parties in these
circumstances as a way of emphasizing the poor state of the world.
Conditional Incumbent Party Hypothesis: Incumbent parties use higher levels of positive
sentiment in their campaign messages than opposition parties. This positive effect of incum-
bency is greater when the economy is performing poorly than when it is performing well.
Empirical Analysis
We test our hypotheses by looking at the strategic use of emotive language in European party manifestos
(Hipt,1990;Hobolt et al.,2013). While much of the research on emotion and politics looks at the use of
images and music, we return to an older tradition that examines how language shapes perceptions of the
political world (Edelman,1964,1977). As studies in linguistics and psychology have shown, language can
engender different emotions (Pennebaker,1993;Pennebaker and Francis,1996), and thereby influence the
frame through which the world is perceived. By focusing on emotive language, our analysis extends the
study of manifestos beyond their traditional use as a means to examine issue salience and party positions.
8

Party Manifestos
Manifestos obviously represent only one type of campaign message. However, they are perhaps the most
important type of campaign message as they contain each party’s official platform. Parties spend consider-
able time deciding which issues to include in their manifestos and how much space to give them (Janda et al.,
1995;Green and Hobolt,2008;Dolezal et al.,2012;Däubler,2012a,b). We suspect that parties are just as
strategic about the emotive language they include. This is because “parties make determined efforts to cam-
paign based on their . . .manifestos”, and because the language and campaign messages found in manifestos
are repeated when parties “communicate to the public via other avenues, such as campaign advertisements,
party elites’ campaign speeches, and media interviews” (Adams, Ezrow and Somer-Topcu,2011, 372). A
consequence of this last point is that voters are exposed to the campaign messages found in manifestos even
if they do not explicitly read these documents. The importance of manifestos is also reflected in the fact that
they play an important role in the government formation process (Däubler,2012a) and that governmental
parties make concerted efforts to implement their manifesto campaign pledges (Thomson et al.,2017).
Although it is often assumed that the electorate is uninterested in party manifestos, some voters do
consult these documents. The German Election Study, for example, found that 32% of the public claimed to
have read manifestos prior to the 2013 elections (D’Ottavio and Saalfeld,2016). Similarly, a poll in the UK
found that 27% of respondents claimed to have looked at party manifestos leading up to the 2010 elections
(Dathan,2015). Further evidence voters actively seek out manifestos comes from online searches for these
documents. Figure 2presents data from the UK between 2004 and 2017 showing the frequency with which
people used Google to search for the Conservative Party, the Labour Party, and the Liberal Party (dashed
gray lines) relative to the frequency with which they used it to search for party manifestos (solid blue lines).4
Naturally, individuals are much more likely to use a party name as their search term than a party manifesto.
The important thing to note, though, is that the relative frequency with which people searched for manifestos
increased substantially (the blue upticks) just prior to the May 2005, 2010, 2015 and June 2017 elections.5
4A limitation of Google search term data is that it provides a relative, rather than absolute, measure of search term traffic. This
means we can only interpret the data for a party manifesto search term relative to some second search term. In Figure 2we use
a party’s name as a natural second ‘anchor’ search term. The vertical axes, Google search popularity, are scaled from 0 to 100,
so that 100 represents the highest number of searches in a month that were conducted for the anchor search term between 2004
and 2017. The number of searches per month for both the party name search term and the party manifesto search term are then
measured relative to this ‘highest’ value. Thus, a Google search popularity score of 20 indicates that people used this search term
at one fifth the rate that they used the most popular search term in its most ‘popular’ month.
5Given that many people access manifestos directly from party websites, which they reach by searching on a party name, the
information shown in Figure 2is almost certainly an underestimate of the extent to which voters seek out manifestos.
9

Figure 2: Google Searches for Party Names and Party Manifestos in the United Kingdom, 2004-2017
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
0 20 40 60 80 100
Conservative Party
Time
Google Search Popularity
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
0 20 40 60 80 100
Labour Party
Time
Google Search Popularity
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
0 20 40 60 80 100
Liberal Party and Liberal Democrats
Time
Google Search Popularity
Note: Figure 2indicates the frequency with which individuals used Google to search for the Conservative Party, the Labour Party, and the Liberal
Party (dashed lines) relative to the frequency with which they used it to search for party manifestos (solid lines).
Significantly, those individuals who actively seek out manifestos tend to be more politically sophisticated
than the average voter and thus opinion makers in their social networks (Kenny,1998;Christakis and Fowler,
2009). This again means we can expect the impact of the emotive language used in manifestos to be felt far
beyond the set of individuals who explicitly read these documents.6
Manifestos have at least four desirable properties for testing our hypotheses. First, they provide
6We recognize there is no strong consensus as to the overall reach of manifestos into the electorate. Importantly, if only a few
voters are exposed to the information in manifestos, then this works against us finding support for our hypotheses. This is because
our theory is premised on parties having strategic incentives to use emotive language to shape voter perceptions of the state of the
world. If the campaign messages in manifestos are not expected to reach voters, parties will have fewer incentives to use emotive
language strategically and it becomes less likely we will find the patterns we predict in the data. In effect, party manifestos may
well represent a difficult case for us.
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parties with an opportunity to place their campaign strategy before voters in a carefully scripted way that is
unfiltered by the media. This is important because our theory focuses on the strategic choices parties make
with respect to their use of emotive language, and not on how party campaign messages are portrayed by
the media. Parties do not exert the same degree of control over other types of campaign messages. For
example, the content and style of televised debates is rarely under the control of individual parties, and
party leaders often find themselves responding on the fly to the issues and questions raised by, and language
and gestures used by, debate moderators, political opponents, and audience members. Second, manifestos
outline the overarching campaign strategy of parties in a way that, say, party press releases or party election
broadcasts, which often emerge irregularly throughout the campaign in response to ad hoc developments,
might not. Third, manifestos are a type of campaign message that is used across Europe, thereby facilitating
cross-national comparison. This is not true of other forms of campaign message. Unlike many countries,
for example, Switzerland forbids political advertising on television and the radio, and parties generally
conduct their campaigns in newspapers and on election posters. Other countries allow televised advertising,
but there is considerable cross-national heterogeneity in how it is regulated (Holtz-Bacha and Just,2017).
Similar variation exists when it comes to election debates or the extent to which parties and their candidates
use websites and social media (Gibson,2004;Gibson and Römmele,2009). Fourth, European manifestos
are available for a long period of time, something that allows us to examine how the same parties change
their use of campaign sentiment as they move in and out of office.7
Our dataset comprises 421 manifestos from 108 distinct parties between 1980 and 2012 from eight
countries: France, Germany, Ireland, Italy, Netherlands, Portugal, Spain, and the United Kingdom. Existing
studies that examine the use of emotion in election campaigns typically focus on individual countries, espe-
cially the United States. Our analysis is one of the first to adopt an explicitly cross-national perspective. We
focus on this particular set of countries largely for computational reasons — we can only create our mea-
sures of campaign sentiment for manifestos written in English, Dutch, French, German, Italian, Portuguese,
and Spanish. Almost all of our countries have experienced coalition governments. This is important as our
Prime Ministerial Party Hypothesis requires us to test the claim that prime ministerial parties exhibit higher
levels of positive sentiment than their coalition partners. Party manifestos were obtained from the Political
7Although manifestos have several desirable properties for testing our hypotheses, we do examine the strategic use of emotive
language in other types of campaign messages – televised election debates, party election broadcasts, and party websites – in a
case study of the 2013 German elections in Online Appendix D. The results are remarkably similar to those presented in the main
text and in line with our theoretical predictions. Among other things, these supplementary analyses provide further support for the
claim that parties adopt a consistent message across different forms of campaign media (Adams, Ezrow and Somer-Topcu,2011).
11

Documents Archive (Benoit, Bräuninger and Debus,2009), which includes manifestos for all parties that
win at least 1% of the valid votes in the election for which the manifesto was written. Our corpus of man-
ifestos spans 70 national elections. The average manifesto contains 21,979 words and 879 sentences. In
total, our manifestos comprise 9,274,954 words.
Consistent with salience theory, research has shown that parties rarely use manifestos to target their
opponents (Budge and Farlie,1983a,b;Dolezal et al.,2014). Instead, they use them to focus on their own
policies and valence characteristics. As we demonstrate, though, manifestos exhibit considerable variation
in the extent to which they include positive and negative emotive language. This provides further support
for our earlier claim that campaign sentiment is both conceptually and empirically distinct from the two
traditional dimensions of election campaigns shown in Figure 1.
Measuring Campaign Sentiment
We measure campaign sentiment using the Linguistic Inquiry and Word Count (LIWC) program (Pen-
nebaker, Booth and Francis,2007).8This is a tool for conducting automatic sentiment analysis widely
used in the social sciences and increasingly in political science (Bryan and Ringsmuth,2016;Corley and
Wedeking,2014;Owens and Wedeking,2011,2012;Settle et al.,2016). The program scans documents and
uses a language-specific dictionary to assign each word to one or more categories.9Each category groups
words that share similar linguistic dimensions. For example, categories might be pronouns or verbs, psy-
chological constructs such as affect or cognition, concern categories such as work or home, or linguistic
dimensions. As the program scans a document, it increments the count of words belonging to each category.
It then divides the final counts by the total number of words in the document, creating a measure of the per-
centage of words belonging to each category. As an example, LIWC could analyze a document and report
that 15% of the words are verbs. Researchers have repeatedly verified that the LIWC categories accurately
measure these underlying linguistic constructs. In particular, research has shown that LIWC categories have
strong predictive, concurrent, and convergent validity (Pennebaker and Francis,1996;Alpers et al.,2005;
Pennebaker, Booth and Francis,2007).10
8LIWC can be implemented directly or via quanteda, an Rpackage designed to help manage and analyze text (Benoit,2017).
9The English dictionary includes almost 4,500 words or word stems. It has been estimated that, on average, these words account
for over 86% of the words people use in various forms of writing and speech (Pennebaker et al.,2007, 10).
10LIWC can clearly misclassify individual words, particularly those that are used in an ironic or sarcastic manner (Tausczik and
Pennebaker,2010, 30). However, these errors rarely affect results at the document level as LIWC uses a probabilistic model that
classifies words based on how they are most commonly used. LIWC does better at analyzing longer texts than shorter ones. That
the average manifesto contains about 22,000 words means that LIWC should provide accurate results in our particular application.
12

Two LIWC categories are of particular interest: (i) positive emotive words and (ii) negative emotive
words. Each category is mutually exclusive in that words in one category do not appear in the other. Most
words we use have no emotional valence and, as a result, the scores for both categories are relatively low in
all types of documents. In Table 1, we show the mean percentage of positive and negative words for different
types of text written in English. The mean percentage of positive words ranges from 1.33 (scientific articles)
to 3.72 (blogs). The mean percentage of negative words ranges from 0.71 (daily writing) to 2.67 (emotion
writing). In our sample of manifestos, the mean percentage of positive words is 3.02 (σ= 1.91) and the
mean percentage of negative words is 1.32 (σ= 0.79).11
Table 1: Mean Positive Words Scores and Negative Words Scores
Party Manifestos Emotion Writing Daily Writing Scientific Articles Blogs Novels Talking
Positive Words 3.02 3.28 1.83 1.33 3.72 2.86 3.42
Negative Words 1.32 2.67 0.71 0.84 2.07 1.98 1.49
Note: The first column contains the mean percentages from our party manifestos. The remaining columns present the mean
percentages across a range of English language texts (Pennebaker, Booth and Francis,2007, 9-13).
To better understand these two categories, consider the English dictionary. The positive words cat-
egory contains 406 words such as efficient,good, or improve. The sentence below comes from the UK
Conservative Party’s manifesto in 1987. Positive words are shown in bold.
In the last eight years our country has changed — changed for the better.
If we were to code this sentence as the whole document, the positive words score would be 7.69, indicating
that 1/13 = 7.69% of the words are positive. The negative words category contains 499 words, such as
beaten,danger, or unimpressive. The sentence below comes from the UK Liberal Party’s manifesto in
1987. Negative words are underlined and shown in bold.
Too many elderly people suffer from isolation,fear and cold.
Ultimately, concerns with the misclassification of words relate to potential measurement error in our dependent variable. Signif-
icantly, this type of measurement error does not affect the unbiasedness of one’s parameter estimates; it simply leads to larger
variances than would otherwise be the case. In other words, any measurement error resulting from the LIWC program will only
make it harder for us to find statistically significant results. Finally, we recognize there is other software that can conduct automatic
sentiment analysis, such as AFINN,ANEW,Stanford’s NLP, and WordNet-Affect. However, these programs are limited to only a
few languages, typically English and Chinese, and do not have LIWC’s long history of validation both within and across languages.
11More descriptive information for our manifestos can be found in Online Appendix B, which contains histograms of positive
and negative words scores.
13

If we were to code this sentence as the whole document, the negative words score would be 30.00, indicating
that 3/10 = 30.00% of the words are negative.
The levels of positive or negative word scores vary across different languages. This is illustrated by
the boxplots shown in the upper portion of Figure 3. The manifestos written in Portuguese, for example, ex-
hibit much higher levels of both positive and negative words than the manifestos written in other languages.
In our upcoming analyses, we take account of the heterogeneity across languages in the use of positive and
negative words through the use of language fixed effects.
Figure 3: Positive Words Scores,Negative Words Scores, and Positive Sentiment by Language
0
2
4
6
8
10
Positive Words Score
Dutch English French German Italian Portuguese Spanish
(a) Positive Words Score
0
1
2
3
4
5
Negative Words Score
Dutch English French German Italian Portuguese Spanish
(b) Negative Words Score
0
2
4
6
8
Positive Sentiment
Dutch English French German Italian Portuguese Spanish
(c) Positive Sentiment
Ultimately, our hypotheses are concerned with the overall level of positive sentiment exhibited in
a manifesto. Since manifestos contain both positive and negative words, our dependent variable, Positive
Sentiment, is calculated as the positive words score minus the negative words score for a given manifesto.
14

The theoretical range for our dependent variable is +100% if all words were positive to −100% if all words
were negative. In line with the fact that most words lack emotional valence, the observed range for Positive
Sentiment is −0.68% to 7.60%; the mean is 1.70% and the standard deviation is 1.45%. The lower portion
of Figure 3provides boxplots for Positive Sentiment. The manifestos written in Dutch have the lowest mean
levels of Positive Sentiment, while those written in Portuguese have the highest.
Independent Variables
To test our hypotheses, we created two variables capturing a party’s incumbency status. Incumbent Party is a
dichotomous variable that equals 1when the party is in government, 0otherwise. Incumbent Party ×Prime
Ministerial Party is another dichotomous variable that equals 1when the party is the prime ministerial party,
0otherwise.12 Information on a party’s incumbency status comes from Glasgow, Golder and Golder (2011).
We created two variables to evaluate our Extreme Ideology Hypothesis.Left-Right captures a party’s
position on a 0-10 left-right scale as identified by country experts (Döring and Manow,2015). Left-Right2
is a quadratic term designed to test the conditional claim that extremist parties use less positive sentiment
than moderate parties. As an alternative strategy for evaluating our hypothesis, we created a third variable,
Extremist Party, based on a party’s ‘family’. Extremist Party is a dichotomous variable that equals 1if a
party belongs to a party family on the extreme left (communist) or extreme right (far right), 0otherwise.13
Data for this come from the Parliaments and Governments Database (Döring and Manow,2015).
We also created measures of economic performance. We focus on unemployment, inflation, and
growth, because the economic voting literature singles these indicators out as being “related to changes in
support for the government in many countries” (Powell and Whitten,1993, 392). Unemployment is the
unemployment rate (International Monetary Fund,2015), Inflation is the inflation rate (World Bank,2012),
and Growth is the percentage growth in real GDP expenditures from the Penn World Tables 9.0 (Feenstra,
Inklaar and Timmer,2015). We lag these variables by a year to ensure they reflect the economic conditions
at a time prior to when the parties write their manifestos. We also create interactions between each of them
and Incumbent Party to test the conditionality of the Conditional Economic Performance Hypothesis and the
Conditional Incumbent Party Hypothesis.
12We do not need to include a dichotomous variable, Prime Ministerial Party, in our empirical analysis even though it is a
constitutive element of our interaction variable. This is because its inclusion leads to perfect multicollinearity given that Prime
Ministerial Party is only equal to 1when the party is also an incumbent party (Brambor, Clark and Golder,2006, 70, note 8).
13Our results remain robust if we also classify Green parties as extreme left.
15

Model Specification and Results
We test our hypotheses using ordinary least squares with bootstrap standard errors clustered by election. We
cluster the standard errors to take account of the fact that the content and language used in manifestos are
unlikely to be independent in a given election. We employ bootstrap standard errors because the literature
is unclear as to when the number of clusters is sufficiently large to justify the asymptotic assumptions
underlying traditional cluster-robust standard errors (Esarey and Menger,2018;Wooldridge,2003, 135).14
We also include language fixed effects to take account of the fact that users of different languages differ in
their proclivity to employ positive and negative emotive words.15
The results of eleven different models are shown in Table 2. The first two columns focus on the
relationship between positive sentiment and incumbency status. The next two columns add our indicators of
party position. The following three columns add our economic indicators. The last four columns examine
the conditional relationship between incumbency status and our three economic indicators, first separately
and then together. Our models are specified so that the coefficients on the constant terms indicate the
average language fixed effect.16 σuindicates the standard deviation for the language fixed effects, while
σeindicates the standard deviation for the idiosyncratic error terms associated with the manifestos. The
intraclass correlation coefficient, ρ, captures the proportion of the total variance attributable to the language
fixed effects. In line with the information in Figure 3showing the strong impact that language has on the
proclivity to use emotive words, the values of ρreported in Table 2(0.79-0.84) indicate that the language
fixed effects play a large role in explaining the variation we observe in the use of positive sentiment.
As predicted by the Incumbent Party Hypothesis, Model 1 shows that incumbent parties use sig-
nificantly more positive emotive language than opposition parties. This is indicated by the positive and
significant coefficient on Incumbent Party.17 The effect of incumbency is substantively large — positive
sentiment is 34% [24.6%,44.9%] higher for incumbent parties than opposition parties. 95% two-tailed con-
fidence intervals are shown in parentheses. Importantly, the positive and statistically significant coefficient
on Incumbent Party is robust to the use of party fixed effects. This is particularly compelling evidence in
14Results are stronger with traditional cluster-robust standard errors; they are also robust to not clustering the standard errors.
15As Online Appendix C indicates, our results are qualitatively similar if we employ country fixed effects.
16For those who are interested in the individual estimates of the language fixed effects, see Online Appendix C.
17Incumbents arguably have weaker incentives to frame the world in a positive light when there is low clarity of responsibility
(Powell and Whitten,1993). However, there is only limited support for this conjecture in our data. When we add an interaction
term between Incumbent Party and a dichotomous variable for coalition government, we find that the coefficient on the interaction
term is negative, indicating that incumbent parties in coalition governments do use less positive sentiment than those in single-party
governments. However, the coefficient on the interaction term is not statistically significant.
16

Table 2: Positive Sentiment in European Party Manifestos
Dependent Variable: Positive Sentiment
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10 Model 11
Incumbency
Incumbent Party 0.53∗∗∗ 0.36∗∗∗ 0.15∗∗ 0.26∗∗∗ 0.27∗∗∗ 0.24∗∗∗ 0.26∗∗∗ 0.05 0.34∗∗ 0.23∗∗ 0.14
(0.07) (0.08) (0.06) (0.08) (0.08) (0.07) (0.08) (0.11) (0.14) (0.10) (0.16)
Incumbent Party ×Prime Ministerial Party - 0.28∗∗∗ 0.24∗∗∗ 0.24∗∗∗ 0.21∗∗ 0.24∗∗∗ 0.24∗∗∗ 0.23∗∗∗ 0.26∗∗∗ 0.24∗∗∗ 0.24∗∗∗
- (0.07) (0.07) (0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.09)
Ideology
Left-Right - - 0.41∗∗∗ - - - - - - - -
- - (0.07) - - - - - - - -
Left-Right2- - −0.04∗∗∗ - - - - - - - -
- - (0.01) - - - - - - - -
Extremist Party - - - −0.50∗∗∗ −0.49∗∗∗ −0.45∗∗∗ −0.50∗∗∗ −0.47∗∗∗ −0.45∗∗∗ −0.51∗∗∗ −0.43∗∗∗
- - - (0.10) (0.11) (0.11) (0.10) (0.10) (0.11) (0.10) (0.10)
Economic Conditions
Inflation - - - - −0.03∗∗ - - −0.04∗∗∗ - - −0.04∗∗
- - - - (0.01) - - (0.01) - - (0.01)
Unemployment - - - - - −0.03∗∗∗ - - −0.02∗∗ -−0.03∗∗
- - - - - (0.01) - - (0.01) - (0.01)
Growth - - - - - - −0.001 - - -0.004 −0.02
- - - - - - (0.01) - - (0.01) (0.01)
Economic Conditions and Incumbency
Incumbent Party ×Inflation - - - - - - - 0.04∗∗ - - 0.03∗
- - - - - - - (0.02) - - (0.02)
Incumbent Party ×Unemployment - - - - - - - - −0.01 - −0.01
- - - - - - - - (0.02) - (0.02)
Incumbent Party ×Growth - - - - - - - - - 0.01 0.01
- - - - - - - - - (0.02) (0.02)
Constant 1.56∗∗∗ 1.56∗∗∗ 0.77∗∗∗ 1.72∗∗∗ 1.85∗∗∗ 1.94∗∗∗ 1.72∗∗∗ 1.90∗∗∗ 1.92∗∗∗ 1.73∗∗∗ 2.13∗∗∗
(0.05) (0.15) (0.14) (0.16) (0.20) (0.20) (0.17) (0.20) (0.20) (0.16) (0.21)
Language Fixed Effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Manifestos 421 421 382 412 391 405 412 391 405 412 388
Elections 70 70 69 70 64 68 70 64 68 70 63
Within R20.10 0.11 0.18 0.18 0.21 0.19 0.18 0.22 0.19 0.18 0.22
Between R20.001 0.08 0.10 0.16 0.45 0.02 0.17 0.47 0.02 0.17 0.32
Overall R20.03 0.04 0.07 0.03 0.001 0.02 0.03 0.002 0.02 0.03 0.00
σu1.35 1.34 1.39 1.36 1.43 1.40 1.36 1.43 1.40 1.36 1.46
σe0.69 0.69 0.63 0.66 0.66 0.64 0.66 0.65 0.64 0.66 0.63
ρ0.79 0.79 0.83 0.81 0.83 0.83 0.81 0.83 0.83 0.81 0.84
∗p < 0.10;∗∗p < 0.05;∗∗∗ p < 0.01 (two-tailed).
Note: Bootstrap standard errors clustered by election are shown in parentheses.
17

support of our Incumbent Party Hypothesis as it indicates that the same party alters its use of positive sen-
timent in the predicted manner when it moves in and out of office.18 As predicted by the Prime Ministerial
Party Hypothesis, the results in Model 2 indicate that prime ministerial parties adopt even higher levels of
positive sentiment in their manifestos than their coalition partners. This is indicated by the positive and
significant coefficient on Incumbent ×Prime Ministerial Party.
Figure 4provides a graphical summary of our incumbency results. It shows how the predicted level of
Positive Sentiment changes with a party’s incumbency status based on the results in Model 2. The solid blue
lines represent two-tailed 95% confidence intervals.19 Non-prime ministerial incumbent parties exhibit 23%
[12.9%,34.5%] more positive sentiment than opposition parties. Prime ministerial incumbent parties ex-
hibit 41% [30%,53.8%] more positive sentiment than opposition parties. And prime ministerial incumbent
parties exhibit 18% [8.8%,27.5%] more positive sentiment than non-prime ministerial incumbent parties.20
Figure 4: Positive Sentiment and a Party’s Incumbency Status
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
Positive Sentiment
Opposition Party Non-PM Incumbent Party PM Incumbent Party
Note: Figure 4plots the predicted level of Positive Sentiment conditional on incumbency status based on Model 2 in Table 2. The lines represent
two-tailed 95% confidence intervals.
18To feasibly use party fixed effects, we need sufficient within-party variation in our covariates over time. Although limited, we
have just enough variation on a party’s incumbency status to be able to employ party fixed effects for the specification shown in
Model 1. Of the 108 parties for which we have manifestos, 32 exhibit variation in their incumbency status, with 22 having been
incumbents more than once. Unfortunately, we do not have sufficient within-party variation (or indeed any variation for covariates
such as Extremist Party) to feasibly employ party fixed effects in our other models.
19All of the subsequent figures employ two-tailed 95% confidence intervals. We provide equivalent figures with two-tailed 90%
confidence intervals in Online Appendix E.
20The confidence intervals in Figure 4overlap slightly. However, overlapping confidence intervals are not necessarily evidence
18

These results are qualitatively similar across all the models in Table 2.21 Overall, our results with respect to
incumbency status are strongly supportive of our theoretical argument. They suggest that parties think and
act strategically, not only about the substantive content of their party manifestos, but also about the emotive
language they use to convey that content. Our results speak directly to empirical studies finding that voters
hold prime ministerial parties more responsible for the state of the world than their coalition partners (Duch
and Stevenson,2008,2013;Debus, Stegmaier and Tosun,2014;Duch, Przepiorka and Stevenson,2015).
This is because they suggest that prime ministerial parties are aware of this voter behavior and alter their
campaign strategy in response by adopting more positive sentiment than their coalition partners.
As predicted by the Extreme Ideology Hypothesis, ideologically extreme parties use less positive
sentiment than moderate parties. This is indicated by the positive and significant coefficient on Left-Right
and the negative and significant coefficient on Left-Right2in Model 3. Together these coefficients indicate
that positive sentiment first rises and then falls as a party’s position moves across the policy space. This is
graphically illustrated in Figure 5. The solid black line indicates the predicted level of positive sentiment
exhibited by opposition parties based on Model 3.22 The black vertical axis on the left indicates the predicted
value of Positive Sentiment. The gray vertical axis on the right pertains to the histogram and indicates the
percentage of observations at different values of Left-Right. Positive sentiment is maximized when a party’s
policy position is at 5.45 and declines sharply as a party’s position moves towards either the extreme left or
right. This is exactly in line with our theoretical story.
Further support for the Extreme Ideology Hypothesis comes from Model 4. As predicted, the coeffi-
cient on Extremist Party is negative and significant, indicating that ideologically extreme parties exhibit less
positive sentiment than moderate parties. Again, this effect is substantively large. For example, Model 4 in-
dicates that extremist opposition parties employ 29.3% [18.6%,40%] less positive sentiment than moderate
opposition parties. Our results with respect to how a party’s policy position influences its level of positive
sentiment are qualitatively similar across all the models in Table 2.23
that the differences between point estimates are statistically insignificant (Schenker and Gentleman,2001). Indeed, we know that
these differences are significant as the coefficients on Incumbent Party and Incumbent Party ×Prime Ministerial Party in Model 2
are both statistically significant (p < 0.001).
21Not too much should be read into the statistically insignificant coefficients on Incumbent Party in Models 8 and 11, as these
coefficients capture the effect of being a non-prime ministerial incumbent party when inflation (as well as unemployment and
growth) is zero.
22The shape of this black line is the same for incumbent parties. The only difference is that the line would be shifted up to
reflect the higher level of positive sentiment exhibited by incumbent parties, something indicated by the positive and statistically
significant coefficients on Incumbent Party and Incumbent Party ×Prime Ministerial Party in Model 3.
23To maximize our sample size when evaluating our Extreme Ideology Hypothesis, we focus on the dichotomous Extremist Party
19

Figure 5: Positive Sentiment and a Party’s Left-Right Policy Position
.4
.6
.8
1
1.2
1.4
1.6
1.8
2
2.2
Positive Sentiment
0
5
10
15
20
Percentage of Observations
0 1 2 3 4 5 6 7 8 9 10
Left-Right Position
Note: Figure 5plots the predicted level of Positive Sentiment for opposition parties across the left-right policy space based on Model 3 in Table 2.
The dashed lines represent two-tailed 95% confidence intervals.
In line with the Economic Performance Hypothesis, parties adopt less positive sentiment when the
economy is performing poorly with respect to inflation and unemployment. This is indicated by the negative
and significant coefficients on Inflation in Model 5 and Unemployment in Model 6. These particular results
suggest that campaign sentiment does vary in line with objective economic conditions, just as the standard
economic voting framework would lead us to expect. There is no evidence, however, that positive sentiment
varies with economic growth. This is indicated by the substantively small and insignificant coefficient on
Growth in Model 7. Interestingly, our results with respect to economic conditions are entirely consistent with
previous research showing that the extent to which parties emphasize economic issues in their manifestos
varies systematically with inflation and unemployment but not with economic growth (Williams, Seki and
Whitten,2016). Combining these two sets of results indicates that objective economic conditions (inflation,
unemployment) influence not only how much space parties give to economic issues in their manifestos but
also the emotive content of the language that parties use to convey their campaign messages.
Does the effect of objective economic conditions vary with incumbency status as the Conditional
Economic Performance Hypothesis predicts? Strong support for this exists for inflation. This is indicated by
the negative and significant coefficient on Inflation and the positive and significant coefficient on Incumbent
variable in Models 4-11. However, our inferences are robust to substituting in our Left-Right and Left-Right2variables instead.
20

Party ×Inflation in Model 8. To evaluate the conditional effect of economic performance and incumbency
status in more detail, Figure 6(a) plots the effect of a one standard deviation increase in inflation on Positive
Sentiment for opposition and incumbent parties. Inflation has a strong negative and significant effect on
positive sentiment for opposition parties. Although the effect of inflation remains negative for incumbent
parties, it is much smaller and is no longer significant. This is consistent with our claim that incumbent
parties use positive campaign sentiment to frame poor economic performance in as good a light as they can
whereas opposition parties try to frame it in as bad a light as they can.
Figure 6: The Effect of Objective Economic Indicators on Positive Sentiment conditional on Incumbency
Status
-.4
-.3
-.2
-.1
0
.1
.2
Effect of Inflation on Positive Sentiment
Opposition Party Incumbent Party
(a) Inflation
-.3
-.2
-.1
0
Effect of Unemployment on Positive Sentiment
Opposition Party Incumbent Party
(b) Unemployment
Note: Panel (a) shows the effect of a one standard deviation increase in inflation on Positive Sentiment for opposition and incumbent parties based
on Model 8 in Table 2. Panel (b) shows the effect of a one standard deviation increase in unemployment on Positive Sentiment for opposition and
incumbent parties based on Model 9. The lines represent two-tailed 95% confidence intervals. The coefficient on Incumbent Party ×Inflation is
0.04 (0.02), while the coefficient on Incumbent Party ×Unemployment is −0.01 (0.02); standard errors are shown in parentheses.
There is no support for the Conditional Economic Performance Hypothesis when we focus on unem-
ployment. The results in Model 8 indicate that unemployment always reduces positive sentiment. However,
the magnitude of this effect does not vary with incumbency status. This is indicated by the negative and sig-
nificant coefficient on Unemployment and the insignificant coefficient on Incumbent Party ×Unemployment.
As Figure 6(b) visually demonstrates, a one standard deviation increase in unemployment has a similarly
sized negative effect on positive sentiment for both opposition and incumbent parties — the two confidence
intervals overlap almost entirely. As Model 11 indicates, our results with respect to inflation and unem-
ployment are robust to including all three of our measures of objective economic performance in the same
21

specification.24 That we obtain slightly different conditional results with respect to inflation as opposed
to unemployment suggests that parties may feel they can use emotive language to frame some economic
conditions more than others. One interpretation is that incumbent parties feel free to ignore inflation when
it comes to the emotive content of their campaign messages but not unemployment.
Our last hypothesis, the Conditional Incumbent Party Hypothesis, has to do with how the effect of
incumbency status varies with objective economic conditions. Recall that we expect the positive effect of
incumbency on campaign sentiment to be greater when the economy is performing poorly. We obtain strong
support for this when we focus on inflation. This is indicated by the positive and significant coefficient on
Incumbent Party ×Inflation in Model 8. In Figure 7, we plot the effect of being the incumbent prime min-
isterial party on positive sentiment across the observed range of inflation. As predicted, this marginal effect,
which is always positive and significant, grows in magnitude with higher rates of inflation. We do not ob-
tain such strong support for the Conditional Incumbent Party Hypothesis when we focus on unemployment.
Figure 7: The Effect of Incumbency Status on Positive Sentiment conditional on Inflation
-.5
0
.5
1
1.5
2
Effect of Incumbency on Positive Sentiment
0
5
10
15
20
25
30
35
Percentage of Inflation Observations
0 5 10 15 20 25 30
Inflation
Note: Figure 7shows the effect of being the incumbent prime ministerial party on Positive Sentiment across the observed range of inflation based
on Model 8 in Table 2. The dashed lines represent two-tailed 95% confidence intervals.
24We do not examine the conditional effect of economic growth in Figure 6. Consistent with our previous discussion, there is no
evidence that growth ever has a significant effect on positive sentiment. This is indicated by the insignificant coefficients on Growth
and Incumbent Party ×Growth in Models 10 and 11.
22

While we find that incumbency status always increases positive campaign sentiment as predicted, we do not
find that the magnitude of this effect increases with unemployment. This is indicated by the insignificant
coefficient on Incumbent Party ×Unemployment in Model 9.
Conclusion
Scholars have recently shown that campaigns can engender different types of emotion and thereby shape
voter behavior and perceptions of the world in predictable ways. An implication of this is that political
parties have incentives to be strategic not only about the substantive content of their campaigns but also
about the kind of sentiment they use to convey that content. Some parties should adopt sentiment that
frames the world in a positive light, whereas others should adopt sentiment that frames it in a negative light.
Building on the logic underpinning models of retrospective voting, we employed a novel dataset on
the emotive language used in over 400 European party manifestos to examine how the level of positive
sentiment exhibited by political parties depends on their incumbency status, policy position, and objective
economic conditions. As predicted, incumbent parties, especially prime ministerial parties, exhibit greater
positive sentiment than opposition parties. Also in line with our expectations, we found that ideologically
extreme parties adopt much less positive sentiment than moderate parties, and that all parties adopt sig-
nificantly less positive sentiment when objective economic conditions are poor. These results suggest that
parties are indeed strategic about the type of emotive language they employ in their manifestos. Our case
study of the 2013 German elections in Online Appendix D provides evidence that parties are also strategic
with respect to their use of emotive language in other types of campaign messages.
Our findings have important implications for the study of election campaigns and party strategies.
First, scholars have conceptualized campaigns along two primary dimensions. The campaign content di-
mension captures whether parties compete on policy or valence. The campaign focus dimension captures
whether parties focus their campaigns on themselves or their opponents. We have argued that campaign
sentiment, which captures the emotive content of campaigns, represents a conceptually and empirically dis-
tinct third dimension. Campaigns are about what parties say, who they say it about, and how they say it.
In effect, political parties have a larger arsenal of campaign strategies available to them than is assumed
in the existing literature. While recent studies have demonstrated that campaign sentiment can influence
voter behavior in predictable ways, our analysis is the first to show that political parties deploy campaign
23

sentiment in a strategic manner in multiparty contexts.
Second, our argument provides a possible explanation for why people hold different perceptions of
objective economic conditions and why these differing perceptions are frequently tied to an individual’s
partisan identity (MacKuen, Erikson and Stimson,1989;Duch, Palmer and Anderson,2000;Anderson,
2007;Enns, Kellstedt and McAvoy,2012). While our findings suggest that parties use campaign sentiment
to strategically frame the state of the world, they are not necessarily inconsistent with research showing
that voters generally respond to objective economic reality (Lewis-Beck, Nadeau and Elias,2008;Nadeau,
Lewis-Beck and Éric Bélanger,2013;Lewis-Beck, Martini and Kiewiet,2013). As Gelman and King (1993)
note, high-information and balanced electoral campaigns between parties with competing strategic interests
can produce ‘enlightened preferences’ on the part of voters.
Although the strategic use of campaign sentiment helps to explain the divergent perceptions of the
economy among voters, our findings are encouraging in that they also indicate that election campaigns
are not completely devoid of information. That all parties use less positive sentiment when the economy
is performing poorly suggests that objective economic conditions constrain the strategic use of campaign
sentiment. In effect, campaigns retain some of their information content despite the incentives parties have to
manipulate the emotional responses of voters. Viewed in this light, the advent of ‘fake news’ and campaigns
of deliberate misinformation are a cause for concern, in that these developments may serve to weaken the
constraints offered by objective economic conditions and thereby provide parties with more room to engage
in the strategic manipulation of voter emotions.
Third, scholars typically examine campaign strategy at the party- or candidate-level. Several studies,
for example, claim that trailing candidates are more likely to adopt ‘attack campaigns’ than front-runners
(Skaperdas and Grofman,1995). Relatively little attention is paid to how the broader electoral context in
which parties compete constrains their strategic choices. Our finding that objective economic conditions
constrain the strategic use of campaign sentiment suggests that an election’s macroeconomic context affects
the choices parties make with respect to their campaign strategy. As such, studies of campaign strategy that
cover multiple elections should pay greater attention to the context in which their elections take place.
Fourth, the strategic use of campaign sentiment by political parties has implications for democratic
accountability. If voters are susceptible to the manipulation of campaign sentiment, then the link between
government performance and the electoral success of incumbent parties is weakened. Whether this ulti-
mately helps or harms the reelection prospects of government parties is, however, unclear. As we have
24

argued, incumbent parties have an incentive to employ positive campaign sentiment to portray the world in
the best possible light. To the extent that scholars have empirically examined the role of emotions in pol-
itics, most have focused on negative sentiment and the effectiveness of messages that trigger fear or anger
(Merolla and Zechmeister,2009). We know much less about the effectiveness of messages designed to con-
vey positive sentiment. As a result, we need more research to assess whether, or when, the use of campaign
sentiment disadvantages incumbent parties.
We still know relatively little about the strategic use of emotive content in election campaigns. Here
we have focused on the use of broad emotive categories — positive and negative sentiment. Future research
might fruitfully focus on whether parties are strategic with respect to their use of more specific emotions such
as fear, anger, or enthusiasm. Alternatively, scholars could look at whether the overall amount of emotive
content in election campaigns has changed over time. Do some parties, such as populist parties or those
with charismatic leaders, use more emotion in their campaigns than others? How do parties respond to the
emotive content in their rivals’ campaigns? Does the emotive content of a party’s current election campaign
depend on how that party performed in the previous election? To a large extent, the field of research looking
at the strategic use of campaign sentiment is wide open.
25

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31

Online Appendix A: Finance Ministry Party
The Prime Ministerial Party Hypothesis states that prime ministerial parties use higher levels of positive
sentiment in their campaign messages than their coalition partners. Voters are likely to hold the prime
ministerial party more responsible for the state of the world than its coalition partners. This is because the
prime minister is the most visible member of the government and because the prime ministerial party is
widely recognized as the agenda setter (Glasgow, Golder and Golder,2011;Fortunato, Lin and Stevenson,
2013;Duch and Stevenson,2013). Consistent with this, empirical evidence shows that the economic vote
for the prime ministerial party is disproportionately high compared to that of other governmental parties
(Duch and Stevenson,2008;Debus, Stegmaier and Tosun,2014).
Some scholars have suggested that voters may also attribute responsibility for the state of the world to
the finance ministry party, particularly when it comes to the state of the economy (Williams, Seki and Whit-
ten,2016). However, the empirical support for this claim is rather mixed. For example, Debus, Stegmaier
and Tosun (2014) find that there is no economic vote for the finance ministry party in Germany. In their
more comprehensive study, Duch and Stevenson (2008, 269) conclude that while the finance ministry party
experiences some of the economic vote, “most of it goes to the prime ministerial party.” We claimed in the
main text (see note 3) that, consistent with these previous studies, there is little evidence that parties con-
trolling the finance ministry use higher levels of positive sentiment in their campaign messages than their
coalition partners. We now turn to the basis for our claim.
In Table 3, we present the results from four different models where we examine the level of positive
campaign sentiment found in the manifestos of incumbent parties, incumbent prime ministerial parties,
and incumbent finance ministry parties. Data on incumbent finance ministry parties comes from Seki and
Williams (2014). Model 1 in Table 3acts as a baseline and simply reports the results from Model 2 in Table
2. While the results in Model 2 in Table 3indicate that the level of positive sentiment exhibited by finance
ministry parties is not significantly different from that exhibited by its coalition partners as a whole, those
in Model 3 indicate that finance ministry parties still do not exhibit higher levels of positive sentiment than
their coalition partners even when we separate out prime ministerial parties. These inferences are based on
the fact that the coefficients on Incumbent Party×Finance Ministry Party are not statistically significant in
either Model 2 or Model 3.
The additional interaction term in Model 4 allows us to examine whether the level of positive senti-
1

Table 3: Positive Sentiment in European Party Manifestos
Dependent Variable: Level of Positive Sentiment in a Party Manifesto
Model 1 Model 2 Model 3 Model 4
Incumbency
Incumbent Party 0.36∗∗∗ 0.48∗∗∗ 0.36∗∗∗ 0.39∗∗∗
(0.08) (0.08) (0.08) (0.10)
Incumbent Party×Prime Ministerial Party 0.28∗∗∗ - 0.28∗∗∗ 0.23∗∗∗
(0.07) - (0.08) (0.11)
Incumbent Party×Finance Ministry Party - 0.08 −0.01 −0.09
- (0.09) (0.09) (0.14)
Incumbent PM Party ×Incumbent FM Party - - - 0.12
- - - (0.19)
Constant 1.56∗∗∗ 1.56∗∗∗ 1.56∗∗∗ 1.56∗∗∗
(0.15) (0.15) (0.15) (0.15)
Language Fixed Effects Yes Yes Yes Yes
Manifestos 421 421 421 421
Elections 70 70 70 70
Within R20.11 0.10 0.11 0.11
Between R20.08 0.004 0.08 0.09
Overall R20.04 0.03 0.04 0.04
σu1.34 1.35 1.34 1.34
σe0.69 0.69 0.69 0.69
ρ0.79 0.79 0.79 0.79
*p < 0.10; ** p < 0.05; *** p < 0.01 (two-tailed).
Note: Bootstrap standard errors clustered by election are shown in parentheses. Data come from 421 party manifestos in 70
national legislative elections in eight West European countries from 1980 to 2012. The dependent variable, Positive Sentiment, is
calculated as the percentage of positive emotive words in a manifesto minus the percentage of negative emotive words in a mani-
festo. Incumbent PM Party is equal to Incumbent Party×Prime Ministerial Party and Incumbent FM Party is equal to Incumbent
Party×Finance Ministry Party.
ment exhibited by a party in its manifesto depends on whether it controls both the finance ministry and the
prime ministership or just the finance ministry but not the prime ministership. In our sample, there are 14
observations where a party controls the finance ministry but not the prime ministership and 21 observations
where a party controls the prime ministership but not the finance ministry. The results in Model 4 show that
controlling the finance ministry, either alone or in combination with the prime ministership, never changes
the level of positive sentiment in a party’s manifesto. This is indicated by the statistically insignificant coef-
ficients on both Incumbent Party×Finance Ministry Party and Incumbent PM Party×Incumbent FM Party.
Consistent with the Prime Ministerial Party Hypothesis and the discussion in the main text, though, the
results presented in Table 3indicate that prime ministerial parties always exhibit higher levels of positive
sentiment in their manifestos than their coalition partners, even when they do not control the finance min-
istry. This is indicated by the positive and statistically significant coefficients on Incumbent Party×Prime
Ministerial Party.
2

Online Appendix B: Positive Sentiment and Positive and Negative Words Scores
In Online Appendix B, we provide more descriptive information on our measure of positive campaign sen-
timent. Recall that Positive Sentiment is calculated as the positive words score for a manifesto minus that
manifesto’s negative words score.Positive words scores refer to the percentage of positive emotive words in
a manifesto, while negative words scores refer to the percentage of negative emotive words in a manifesto.
The observed range for Positive Sentiment in our sample is −0.68% to 7.60%; the mean is 1.70% and the
standard deviation is 1.45%. The observed range for positive words score is 0.64% to 9.62%; the mean is
3.02% and the standard deviation is 1.91%. The observed range for negative words score is 0% to 5.22%;
the mean is 1.32% and the standard deviation is 0.79%.
Figure 8: Histograms of Positive Sentiment and Positive and Negative Words Scores
0
.1
.2
.3
.4
Density
0246810
Positive Words Scores
(a)
0
.2
.4
.6
.8
Density
012345
Negative Words Scores
(b)
0
.1
.2
.3
.4
Density
02468
Positive Sentiment
(c)
Note: Figure 8shows a series of histograms for positive words scores (panel a), negative words scores (panel b), and Positive Sentiment (panel c)
for 421 party manifestos in 70 national legislative elections in eight West European countries from 1980 to 2012. Positive words scores refer to the
percentage of positive emotive words in a manifesto, while negative words scores refer to the percentage of negative emotive words in a manifesto.
Positive Sentiment is calculated as the positive words score for a manifesto minus that manifesto’s negative words score.
3

Online Appendix C: Fixed Effects
In Appendix C, we further examine the use of fixed effects in our model. In Table 2in the main text, we
present results from a model in which we employed language fixed effects and bootstrap standard errors
clustered by election. The language fixed effects were included to take account of the fact that users of
different languages differ in their underlying proclivity to employ positive and negative emotive words. We
clustered the standard errors on elections to take account of the fact that the content and language used in
party manifestos are unlikely to be independent within a given election. And we used bootstrap clustered
standard errors as a conservative estimate of the size of the standard errors, as the literature is unclear as to
when the number of clusters is sufficiently large to justify the asymptotic properties of traditional cluster-
robust standard errors (Williams,2000;Green and Vavreck,2008;Esarey and Menger,2018;Wooldridge,
2003, 135).1
Language Fixed Effects
There are several different ways to estimate a fixed effects model that produce identical results with respect
to the estimated coefficients and standard errors. In Table 2in the main text, we presented results from the
‘within estimator’ version of the fixed effects model, which treats our language fixed effects as nuisance
parameters and removes them through mean-differencing (Cameron and Trivedi,2009, 251). Our models
were specified so that the coefficients on the constant terms indicated the average language fixed effects. It is
also possible, though, to estimate a least-squares dummy-variable (LSDV) version of the fixed effects model
that provides the individual estimates for the language fixed effects (Cameron and Trivedi,2009, 253). For
those who are interested, we now present the results from an LSDV version of our fixed effects model in
Table 4. The models are specified with no constant so that we can estimate the intercepts for each language.
Consistent with the ‘language’ information displayed in Figure 3in the main text, English and Portuguese
have the two largest fixed effects, while Dutch and Italian have the two smallest fixed effects.
As expected, all of the slope coefficients and standard errors shown in Table 4are identical to those
shown in the main text in Table 2. These are our primary parameters of interest, as they allow us to test our
hypotheses. You’ll notice, though, that the estimates of the R2differ across the two versions of the fixed
effects model. This simply reflects the fact that the R2is calculated differently in the LSDV and the within
1As we note in the main text, our results are slightly stronger if we had employed traditional cluster-robust standard errors. Our
inferences are also robust if we do not cluster our standard errors by election.
4

Table 4: Positive Sentiment in European Party Manifestos – Language LSDV Fixed Effects Model
Dependent Variable: Positive Sentiment
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10 Model 11
Incumbency
Incumbent Party 0.53∗∗∗ 0.36∗∗∗ 0.15∗∗ 0.26∗∗∗ 0.27∗∗∗ 0.24∗∗∗ 0.26∗∗∗ 0.05 0.34∗∗ 0.23∗∗ 0.14
(0.07) (0.08) (0.06) (0.08) (0.08) (0.07) (0.08) (0.11) (0.14) (0.10) (0.16)
Incumbent Party ×Prime Ministerial Party - 0.28∗∗∗ 0.24∗∗∗ 0.24∗∗∗ 0.21∗∗ 0.24∗∗∗ 0.24∗∗∗ 0.23∗∗∗ 0.26∗∗∗ 0.24∗∗∗ 0.24∗∗∗
- (0.07) (0.07) (0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.09)
Ideology
Left-Right - - 0.41∗∗∗ - - - - - - - -
- - (0.07) - - - - - - - -
Left-Right2- - −0.04∗∗∗ - - - - - - - -
- - (0.01) - - - - - - - -
Extremist Party - - - −0.50∗∗∗ −0.49∗∗∗ −0.45∗∗∗ −0.50∗∗∗ −0.47∗∗∗ −0.45∗∗∗ −0.51∗∗∗ −0.43∗∗∗
- - - (0.10) (0.11) (0.11) (0.10) (0.10) (0.11) (0.10) (0.10)
Economic Conditions
Inflation - - - - −0.03∗∗ - - −0.04∗∗∗ - - −0.04∗∗
- - - - (0.01) - - (0.01) - - (0.01)
Unemployment - - - - - −0.03∗∗∗ - - −0.02∗∗ -−0.03∗∗
- - - - - (0.01) - - (0.01) - (0.01)
Growth - - - - - - −0.001 - - -0.004 −0.02
- - - - - - (0.01) - - (0.01) (0.01)
Economic Conditions and Incumbency
Incumbent Party ×Inflation - - - - - - - 0.04∗∗ - - 0.03∗
- - - - - - - (0.02) - - (0.02)
Incumbent Party ×Unemployment - - - - - - - - −0.01 - −0.01
- - - - - - - - (0.02) - (0.02)
Incumbent Party ×Growth - - - - - - - - - 0.01 0.01
- - - - - - - - - (0.02) (0.02)
Language Fixed Effects
Dutch 0.27∗∗∗ 0.28∗∗∗ -0.47∗∗∗ 0.41∗∗∗ 0.49∗∗∗ 0.54∗∗∗ 0.41∗∗∗ 0.55∗∗∗ 0.51∗∗∗ 0.42∗∗∗ 0.68∗∗∗
(0.11) (0.07) (0.15) (0.06) (0.06) (0.08) (0.06) (0.07) (0.09) (0.06) (0.09)
English 2.24∗∗∗ 2.23∗∗∗ 1.35∗∗∗ 2.33∗∗∗ 2.41∗∗∗ 2.60∗∗∗ 2.33∗∗∗ 2.45∗∗∗ 2.57∗∗∗ 2.34∗∗∗ 2.76∗∗∗
(0.11) (0.11) (0.17) (0.10) (0.11) (0.11) (0.11) (0.11) (0.12) (0.11) (0.14)
French 1.41∗∗∗ 1.40∗∗∗ 0.63∗∗∗ 1.58∗∗∗ 1.69∗∗∗ 1.80∗∗∗ 1.58∗∗∗ 1.73∗∗∗ 1.77∗∗∗ 1.58∗∗∗ 1.96∗∗∗
(0.12) (0.12) (0.17) (0.13) (0.12) (0.16) (0.13) (0.12) (0.17) (0.13) (0.16)
German 1.58∗∗∗ 1.59∗∗∗ 0.78∗∗∗ 1.75∗∗∗ 1.82∗∗∗ 1.97∗∗∗ 1.75∗∗∗ 1.88∗∗∗ 1.95∗∗∗ 1.76∗∗∗ 2.11∗∗∗
(0.10) (0.10) (0.20) (0.10) (0.15) (0.13) (0.11) (0.15) (0.14) (0.11) (0.18)
Italian 0.31∗∗∗ 0.32∗∗∗ -0.52∗∗∗ 0.47∗∗∗ 0.65∗∗∗ 0.70∗∗∗ 0.47∗∗∗ 0.70∗∗∗ 0.67∗∗∗ 0.48∗∗∗ 0.94∗∗∗
(0.10) (0.10) (0.17) (0.13) (0.13) (0.17) (0.13) (0.13) (0.18) (0.13) (0.19)
Portuguese 4.26∗∗∗ 4.25∗∗∗ 3.63∗∗∗ 4.46∗∗∗ 4.79∗∗∗ 4.73∗∗∗ 4.46∗∗∗ 4.86∗∗∗ 4.70∗∗∗ 4.47∗∗∗ 5.11∗∗∗
(0.20) (0.20) (0.19) (0.17) (0.13) (0.17) (0.18) (0.13) (0.18) (0.18) (0.17)
Spanish 1.81∗∗∗ 1.79∗∗∗ 0.88∗∗∗ 1.90∗∗∗ 2.04∗∗∗ 2.34∗∗∗ 1.90∗∗∗ 2.09∗∗∗ 2.31∗∗∗ 1.91∗∗∗ 2.55∗∗∗
(0.04) (0.04) (0.15) (0.05) (0.09) (0.20) (0.07) (0.10) (0.21) (0.07) (0.23)
Manifestos 421 421 382 412 391 405 412 391 405 412 388
Elections 70 70 69 70 64 68 70 64 68 70 63
R20.91 0.91 0.93 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92
∗p < 0.10;∗∗p < 0.05;∗∗∗ p < 0.01 (two-tailed).
Note: Bootstrap standard errors clustered by election are shown in parentheses. Data come from 421 party manifestos in 70 national legislative elections in eight West European countries from 1980
to 2012. The dependent variable, Positive Sentiment, is calculated as the percentage of positive emotive words in a manifesto minus the percentage of negative emotive words in a manifesto.
5

estimator models (Cameron and Trivedi,2009, 258). Notably, the estimates of the ‘within R2’ from the
within estimator models are always smaller (never larger) than the equivalent estimates of the R2from the
LSDV models. This is because the ‘within estimator’ models do not take account of the variance explained
by the language fixed effects. There is a debate about the relative merits of the different R2statistics.
We do not wish to take a position in this debate as we are more concerned with hypothesis testing and
evaluating substantive effects than with prediction and model fit, and because there are reasons to question
the informative value of all versions of the R2statistic (King,1986,1990,1991). As a result, we report the
R2from the within estimator models in Table 2in the main text, and for those who are interested we provide
the R2from the LSDV models in Table 4here in Online Appendix C.
The LSDV fixed effects model does not provide estimates of σu,σe, and ρ. Recall that σuindicates
the standard deviation for the language fixed effects, while σeindicates the standard deviation for the id-
iosyncratic error terms associated with the party manifestos. ρis the intraclass correlation coefficient and
can be interpreted as the proportion of the total variance attributable to the language fixed effects.
Country Fixed Effects
In the main text (footnote 15), we noted that our results were robust to employing country fixed effects
instead of language fixed effects. We now demonstrate this by reporting the results from a series of country
fixed effects model specifications in Table 5. We employ the least-squares dummy-variable version of the
fixed effects model with no constant so that we can estimate the intercepts for each country and compare our
results to those shown in Table 4. The only change in the model specifications from the equivalent ones used
in Table 4is that we have separate fixed effects for Ireland and the United Kingdom; recall that in Table
4the observations from Ireland and the United Kingdom shared the same English language fixed effect.
The magnitude and statistical significance of the estimated coefficients in the country fixed effects models
in Table 5are qualitatively similar to the magnitude and statistical significance of the estimated coefficients
in the language fixed effects model in Table 4. If anything, the magnitude of the coefficients on Incumbent
Party is slightly larger in the country fixed effects model. The fact that the coefficients are similar across
the language and country fixed effects models is not surprising given that the coefficients on the United
Kingdom and Ireland country fixed effects are similar and that both sets of coefficients are similar to the
English language fixed effects in Table 4.
6

Table 5: Positive Sentiment in European Party Manifestos – Country LSDV Fixed Effects Model
Dependent Variable: Positive Sentiment
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10 Model 11
Incumbency
Incumbent Party 0.55∗∗∗ 0.40∗∗∗ 0.20∗∗∗ 0.30∗∗∗ 0.30∗∗∗ 0.28∗∗∗ 0.30∗∗∗ 0.09 0.37∗∗∗ 0.27∗∗ 0.15
(0.07) (0.07) (0.07) (0.08) (0.08) (0.07) (0.08) (0.11) (0.13) (0.10) (0.16)
Incumbent Party ×Prime Ministerial Party - 0.24∗∗∗ 0.20∗∗∗ 0.21∗∗∗ 0.18∗∗ 0.21∗∗∗ 0.21∗∗∗ 0.21∗∗∗ 0.23∗∗∗ 0.21∗∗∗ 0.23∗∗∗
- (0.07) (0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.09)
Ideology
Left-Right - - 0.39∗∗∗ - - - - - - - -
- - (0.07) - - - - - - - -
Left-Right2- - −0.04∗∗∗ - - - - - - - -
- - (0.01) - - - - - - - -
Extremist Party - - - −0.48∗∗∗ −0.48∗∗∗ −0.44∗∗∗ −0.48∗∗∗ −0.46∗∗∗ −0.44∗∗∗ −0.48∗∗∗ −0.42∗∗∗
- - - (0.11) (0.11) (0.11) (0.11) (0.10) (0.11) (0.10) (0.10)
Economic Conditions
Inflation - - - - −0.03∗∗ - - −0.04∗∗∗ - - −0.03∗∗
- - - - (0.01) - - (0.01) - - (0.01)
Unemployment - - - - - −0.02∗- - −0.02 - −0.02
- - - - - (0.01) - - (0.01) - (0.01)
Growth - - - - - - 0.004 - - 0.001 −0.01
- - - - - - (0.01) - - (0.01) (0.01)
Economic Conditions and Incumbency
Incumbent Party ×Inflation - - - - - - - 0.04∗∗ - - 0.03∗
- - - - - - - (0.02) - - (0.02)
Incumbent Party ×Unemployment - - - - - - - - −0.01 - −0.01
- - - - - - - - (0.02) - (0.02)
Incumbent Party ×Growth - - - - - - - - - 0.01 0.01
- - - - - - - - - (0.02) (0.02)
Country Fixed Effects
United Kingdom 2.50∗∗∗ 2.49∗∗∗ 1.66∗∗∗ 2.53∗∗∗ 2.60∗∗∗ 2.68∗∗∗ 2.52∗∗∗ 2.64∗∗∗ 2.65∗∗∗ 2.53∗∗∗ 2.79∗∗∗
(0.10) (0.07) (0.15) (0.09) (0.12) (0.12) (0.10) (0.12) (0.13) (0.10) (0.15)
Ireland 1.99∗∗∗ 1.99∗∗∗ 1.19∗∗∗ 2.13∗∗∗ 2.25∗∗∗ 2.36∗∗∗ 2.11∗∗∗ 2.30∗∗∗ 2.34∗∗∗ 2.12∗∗∗ 2.59∗∗∗
(0.12) (0.12) (0.18) (0.12) (0.14) (0.13) (0.13) (0.14) (0.14) (0.13) (0.18)
Netherlands 0.27∗∗∗ 0.28∗∗∗ -0.43∗∗∗ 0.40∗∗∗ 0.48∗∗∗ 0.49∗∗∗ 0.39∗∗∗ 0.53∗∗∗ 0.46∗∗∗ 0.39∗∗∗ 0.63∗∗∗
(0.06) (0.06) (0.15) (0.06) (0.07) (0.08) (0.07) (0.07) (0.09) (0.07) (0.10)
France 1.41∗∗∗ 1.40∗∗∗ 0.67∗∗∗ 1.57∗∗∗ 1.68∗∗∗ 1.72∗∗∗ 1.56∗∗∗ 1.72∗∗∗ 1.69∗∗∗ 1.56∗∗∗ 1.89∗∗∗
(0.12) (0.12) (0.17) (0.13) (0.12) (0.15) (0.13) (0.12) (0.16) (0.13) (0.17)
Spain 1.80∗∗∗ 1.79∗∗∗ 0.93∗∗∗ 1.89∗∗∗ 2.03∗∗∗ 2.20∗∗∗ 1.88∗∗∗ 2.08∗∗∗ 2.17∗∗∗ 1.89∗∗∗ 2.43∗∗∗
(0.04) (0.04) (0.15) (0.05) (0.09) (0.18) (0.06) (0.10) (0.19) (0.06) (0.24)
Portugal 4.25∗∗∗ 4.24∗∗∗ 3.67∗∗∗ 4.45∗∗∗ 4.77∗∗∗ 4.67∗∗∗ 4.43∗∗∗ 4.84∗∗∗ 4.64∗∗∗ 4.44∗∗∗ 5.03∗∗∗
(0.20) (0.20) (0.19) (0.17) (0.13) (0.17) (0.18) (0.14) (0.17) (0.18) (0.18)
Germany 1.57∗∗∗ 1.58∗∗∗ 0.81∗∗∗ 1.73∗∗∗ 1.81∗∗∗ 1.90∗∗∗ 1.72∗∗∗ 1.86∗∗∗ 1.87∗∗∗ 1.73∗∗∗ 2.04∗∗∗
(0.10) (0.10) (0.19) (0.11) (0.15) (0.13) (0.11) (0.15) (0.14) (0.11) (0.18)
Italy 0.31∗∗∗ 0.31∗∗∗ -0.48∗∗∗ 0.45∗∗∗ 0.63∗∗∗ 0.62∗∗∗ 0.44∗∗∗ 0.68∗∗∗ 0.59∗∗∗ 0.45∗∗∗ 0.87∗∗∗
(0.10) (0.04) (0.17) (0.13) (0.13) (0.17) (0.13) (0.13) (0.18) (0.13) (0.20)
Manifestos 421 421 382 412 391 405 412 391 405 412 388
Elections 70 70 69 70 64 68 70 64 68 70 63
R20.91 0.91 0.93 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92
∗p < 0.10;∗∗p < 0.05;∗∗∗ p < 0.01 (two-tailed).
Note: Bootstrap standard errors clustered by election are shown in parentheses. Data come from 421 party manifestos in 70 national legislative elections in eight West European countries from 1980
to 2012. The dependent variable, Positive Sentiment, is calculated as the percentage of positive emotive words in a manifesto minus the percentage of negative emotive words in a manifesto.
7

Online Appendix D: A Case Study of the 2013 Elections in Germany
To further evaluate our argument about the strategic use of campaign sentiment, we now briefly examine the
September 22, 2013 German legislative elections. These elections occurred after the time period covered by
the analyses in the main text and therefore represent a more rigorous ‘out-of-sample’ test of our argument
(Gelman and Hill,2006). At the time of the elections, there was an incumbent coalition government com-
prising the Christian Democrats (CDU/CSU) and Free Democrats (FDP). The prime ministerial position was
held by Chancellor Angela Merkel of the Christian Democrats. The main opposition party was the Social
Democrats (SPD), led by Peer Steinbrück. Of the remaining parties, the Greens, Alternative for Germany
(AfD), the Left Party, and the Pirate Party were the most prominent. While the Greens might reasonably
be considered a mainstream party, this is not the case for the other three parties. The Greens are a left of
center environmental party promoting ecological and social sustainability. The AfD, which was founded in
April 2013, is a right-wing populist party with strong anti-immigrant and eurosceptic tendencies. The Left
Party is a left-wing populist party that traces its roots to the Party of Democratic Socialism (PDS), which
governed communist East Germany during the Cold War. The Pirate Party, which was founded in 2006, is
concerned with enhancing transparency and protecting civil rights in the age of the ‘digital revolution’ and
does not fit easily onto the traditional left-right policy dimension.2
Party Manifestos
As indicated in the main text, party manifestos are the ideal form of campaign message for testing our
hypotheses. This is because manifestos have several desirable properties that are not jointly shared by
other types of campaign message. To summarize, manifestos provide parties with an opportunity to directly
place their campaign strategy before voters in a carefully scripted way that is unfiltered by the media; they
outline the overarching campaign strategy of parties in a way that, say, press releases, which often emerge
irregularly throughout the campaign in response to ad hoc developments, might not; they are a type of
campaign message that is used across Europe, thus facilitating cross-national comparison; and they are
available for a long period of time, thereby allowing us to examine how the same parties change their use of
campaign sentiment over time as they move in and out of office.
An analysis of the seven party manifestos used in the 2013 German elections provides strong support
2Our upcoming results are robust to the exclusion of the Pirate Party.
8

for our theory about the strategic use of campaign sentiment.3In line with our Incumbent Party Hypothesis,
the level of positive sentiment employed by incumbent parties (1.41%) is more than twice as high as that
employed by opposition parties (0.68%).4In line with our Prime Ministerial Party Hypothesis, the level
of positive sentiment employed by the prime ministerial party (1.70%) is 53% higher than that employed
by its coalition partner (1.11%), and the level of positive sentiment employed by the non-prime ministerial
incumbent party is 62% higher than that employed by opposition parties. Finally, in line with our Extreme
Ideology Hypothesis, the level of positive sentiment employed by mainstream parties (1.24%) is almost three
times higher than that employed by the more ideologically extreme parties (0.43%).5
In what follows, we discuss the use of emotive language in some of the other types of campaign
messages – televised election debates, party election broadcasts, and party websites – that were used during
the 2013 German elections. We also elaborate on why these other types of campaign messages are not ideal
for testing our theory. Despite our concerns, the results provide broad support for our theoretical argument.
Televised Election Debates
Many European countries hold televised election debates. While there is some cross-national variation,
it is clear that these debates are major campaign events that are watched by a large number of voters. For
example, the first TV election debate in the UK took place in 2010 and was watched by 9.4 million people on
average, or 37% of the TV watching audience (Deans,2010). The 2017 UK election debate drew a smaller,
but not insignificant, peak audience of 4.7 million viewers (Shepherd,2017). The presidential election
debates that occur in France typically enjoy even higher TV audiences. For example, the 2017 presidential
debate between Emmanuel Macron and Marine Le Pen drew an audience of 16.5 million viewers, more than
60% of the TV watching audience (Chrisafis,2017). The 2013 German election debate between Angela
Merkel and Peer Steinbrück was watched by an estimated 20 million viewers (Evans,2013). Election
debates offer political parties a good opportunity to present themselves and their policy platforms to the
electorate in a partially unmediated way, and might be considered a ‘mini version’ of the election campaign.
3With the exception of the party manifesto published by Alternative for Germany (830 words), each of the manifestos in the
2013 German elections was quite long – the average word count for all seven manifestos was 40,635.
4Recall that the numbers in parentheses capture Positive Sentiment, which is calculated as the difference in the percentage of
positive and negative words in a party manifesto. As indicated in the main text, the level of positive sentiment found in the party
manifestos used in our statistical analyses ranges from −0.68% to 7.60%; the mean is 1.76% with a standard deviation of 1.45%.
As a result, the levels of positive sentiment observed in the 2013 party manifestos in Germany are not unusual.
5As with the upcoming analyses, we do not examine our Economic Performance Hypotheses as the state of the economy was
fixed for all parties in the 2013 German elections.
9

There are at least two reasons why using televised election debates to test our argument about the
strategic use of emotive language in campaign messages is problematic, particularly in comparison to using
party manifestos. First, the substantive content and style of election debates is rarely under the control of
individual parties, and party leaders often find themselves responding on the fly to the issues and questions
raised by, and language used by, debate moderators, their political opponents, and audience members. The
face-to-face nature of campaign debates also encourages an active and confrontational approach that could
reasonably cause candidates to adopt a different style of language to that used elsewhere in the campaign.
Moreover, whereas parties can devote as much attention as they want to particular issues in their manifestos,
election debates often force party leaders to talk about issues that are not central to their particular campaign.
Each of the three election debates that took place in the UK in 2010, for example, focused on a different
topic: domestic, international, and economic affairs. This format and these topics were the result of a
negotiating process between the various political parties and media outlets involved in the 2010 debate.
Second, and more importantly, the heterogeneity in televised election debates, both within and across
countries, as well as the relative novelty of these types of events in many European countries, makes drawing
valid cross-national inferences difficult. Some countries have had televised election debates for many years.
For example, France has held debates for every presidential election since 1974, while Germany has held
them on and off for legislative elections since 1972. Other countries, though, have limited experience with
election debates. The United Kingdom, for instance, has held election debates only since 2010. There is also
significant variation in the number of debates per election and in the parties that are eligible, and who choose,
to participate. Consider the case of the UK. There were three election debates prior to the 2010 elections
in the UK, with only the Conservatives, Labour, and the Liberal Democrats allowed to participate. Prior
to the 2015 elections, there were four debates, each with a different number of parties (ranging from seven
to two) competing. Prior to the 2017 elections, there was just one election debate between the leaders of
seven political parties; the incumbent Conservative prime minister, Theresa May, was absent after refusing
to participate. The absence of incumbent or extremist parties in some of these UK debates means that it is
difficult to test our Incumbent Party,Prime Ministerial Party, and Extreme Ideology Hypotheses.
Germany exhibits similar variation in the format of its election debates. From 1972, Germany started
holding election debates, known as Elefantenrunden, in which all of the party leaders with legislative rep-
resentation were eligible to participate (Anstead,Forthcoming, 9). These debates had no time limits and
could last several hours. Election debates did not occur prior to the 1990, 1994, and 1998 elections, be-
10

cause Chancellor Helmut Kohl refused to participate. Election debates returned in 2002 but now as a ‘duel’
(TV-Duell) between the leaders of the two largest parties – the leaders most likely to become Chancellor.
In 2013, a debate similar to the old Elefantenrunden was added in which the leaders of the remaining leg-
islative parties were able to participate. In 2013, therefore, there was a TV-Duell between the incumbent
Christian Democrat Chancellor, Angela Merkel, and the leader of the Social Democrats, Peer Steinbrück, as
well as a three-way contest (TV-Dreikampf ) between the leaders of the Free Democrats, the Left Party, and
the Greens. As they lacked legislative representation, Alternative for Germany and the Pirate Party were not
eligible to participate in this second debate, making it harder to test our Extreme Ideology Hypothesis.
Our discussion here has focused on election debates in the United Kingdom and Germany. However,
similar variation in debate formats exists in other European countries. As previously indicated, these differ-
ences make it difficult to conduct the types of cross-national analyses that appear in the main text. Indeed,
this helps to partially explain the lack of ‘comparative’ research on televised election debates in the existing
literature more generally. In his recent Scopus literature search, Anstead (Forthcoming, 3) finds that 166
articles were published on televised election debates between 2000 and 2015. Fully 80 of these articles
focused entirely on the United States. Of the remaining articles, only five were ‘comparative.’ All five of
these articles compared only two countries, and in four cases the second country was the United States.
With these provisos in hand, we now briefly examine the strategic use of emotive language in the
debates that took place prior to the September 22, 2013 German elections. The TV-Duell between the
CDU/CSU and the SPD took place on September 1 and lasted 90 minutes. The TV-Dreikampf between the
FDP, the Left Party, and the Greens took place the next day on September 2 and lasted 60 minutes. Both
debates were broadcast on four networks: ARD, ZDF, RTL, and ProSieben. After recording both debates,
we transcribed them, separating out the comments associated with each party. We then ran each set of party
comments through the LIWC automatic sentiment analysis program. The average number of words used by
the parties in the TV-Duell was 6,166; it was 2,754 in the TV-Dreikampf.
The results strongly support our hypotheses. In line with our Incumbent Party Hypothesis, the level
of positive sentiment employed by incumbent parties (1.39%) was almost 60% higher than that employed
by opposition parties (0.87%). In line with our Prime Ministerial Party Hypothesis, the level of positive
sentiment employed by the prime ministerial party (1.67%) was about 50% higher than that employed by
its coalition partner (1.11%), and the level of positive sentiment employed by the non-prime ministerial
incumbent party was 27.6% higher than that employed by the opposition parties. These levels of positive
11

sentiment almost perfectly match those found in the party manifestos. Finally, in line with our Extreme
Ideology Hypothesis, the level of positive sentiment employed by mainstream parties (1.25%) was over
three times higher than that employed by the more ideologically extreme parties (0.39%). The magnitude of
the difference in positive sentiment between the mainstream and extremist parties appears to be substantively
larger during the election debates than in the party manifestos.
The Effect of the Election Debate?
In the main text, we took as our starting point the empirical observation in the existing literature that the
emotive content of campaign messages has an impact on voter behavior (Marcus, Neuman and MacKuen,
2000;Brader,2005,2006;Brader and Marcus,2013;Huddy and Gunnthorsdottir,2000;Roseman, Abelson
and Ewing,1986;Weber, Searles and Ridout,2011;Utych,2018). We also took as a our starting point the
empirical observation that language can engender different emotions (Pennebaker,1993;Pennebaker and
Francis,1996;Tausczik and Pennebaker,2010) and thereby shape individual perceptions of the political
world around them (Edelman,1964,1977). We did not seek to replicate these findings. Instead, we ar-
gued that if these empirical findings were correct, then parties should be strategic in their use of campaign
sentiment. We then set out to test whether this is, indeed, the case.
We now take this opportunity, though, to reanalyze the results of an experiment conducted during
the 2013 election debates in Germany that are consistent with previous empirical findings showing how
campaign sentiment can influence how individuals evaluate the state of the world. The experiment, which
we did not design, was done in the context of the German Longitudinal Election Study that accompanied the
2013 elections. Our data come from the first two waves of a panel study (ZA5709), which asked participants
the same series of questions just prior to (wave 1) and just after (wave 2) the TV-Duell between the leaders
of the CDU and SPD. Several of these questions pertained to the economy and the performance of the
government. This setup can be considered a pre-post experimental design with the debate as the treatment.
If party leaders who use higher levels of positive sentiment engender a more positive outlook towards
the world in their supporters than those who do not, then this would be consistent with the existing empir-
ical literature discussing the impact of campaign sentiment on voter behavior. We know from the debate
that Chancellor Angela Merkel (CDU) employed 25% more positive emotive language than her opponent,
Peer Steinbrück (SPD). As a result, we might expect to see the prime minister’s supporters increase their
evaluation of the economy and the government over the course of the debate more than supporters of her
12

opponent. This is precisely what we find. Specifically, we ran the following regression model,
Evaluationt2−Evaluationt1=β0+β1PM Supporter +, (1)
where Evaluation refers to a respondent’s evaluation of the economy or government performance, t2refers
to the post-debate period, t1refers to the pre-debate period, and PM Supporter is a dichotomous variable,
measured at t1prior to the debate, that equals one if the respondent supports Merkel and 0 if the respondent
supports Steinbrück. For Evaluation, we use three different questions that get at retrospective, current, and
prospective evaluations of the economy, two questions that get at the respondent’s own economic well-being,
and one question evaluating government performance. As predicted, the coefficient on PM Supporter,β1,
is positive in all six cases, indicating that Merkel’s supporters improve their evaluation of the state of the
world during the course of the debate. It is statistically significant when evaluating the state of the current
economy, but does not quite reach conventional levels of statistical significance in the other cases.
We recognize that the design of this particular experiment is not ideal for testing the empirical claim
that motivates our own statistical analysis, namely that the emotive content of campaign messages can
influence voter behavior and their evaluation of the state of the world. For example, it may be the case that
participants are responding to the content of what the two candidates are saying as opposed to the emotive
language through which that content is conveyed. Nonetheless, the results are suggestive, and they are
consistent with the underlying premise that motivates our interest in analyzing the strategic use of campaign
sentiment.
Party Election Broadcasts
As noted in the main text, there is considerable cross-national variation in how political election broadcasts
(PEBs) are regulated on television (Kaid and Holtz-Bacha,2006). Some countries like Switzerland, for
example, ban all forms of political advertising on television (and radio). PEBs are not officially banned in
Denmark, but political actors have historically agreed not to use them for campaigning purposes (Kaid and
Holtz-Bacha,2006, 5). While some countries ban ‘paid’ political advertising on public and commercial
television (France, Portugal, Spain, the United Kingdom), others allow it but only on commercial television
(Germany, Italy, and the Netherlands). Many European countries provide ‘free’, but rationed, political
advertising, typically on public television, but there remains significant heterogeneity, both within and across
13

countries, when it comes to things like the number of slots allocated to parties and the length of individual
broadcasts. This variation makes it difficult to draw valid cross-national inferences about the strategic use
of campaign sentiment from party election broadcasts. Note also that we are interested in the use of emotive
language in campaign messages. As previous research has indicated (Huddy and Gunnthorsdottir,2000;
Brader,2006), much of the emotive content in PEBs comes from the imagery and music that is employed.
From a practical point of view, the limited number of words employed in a typical PEB also raises concerns
about the reliability of automatic sentiment analysis programs like LIWC (see note10).
On the whole, party election broadcasts play only a limited role during German election campaigns.
Indeed, each party typically releases only one broadcast of up to 90 seconds for the entire campaign
(Schultheis,2013). In 2013, the average number of words used in a party election broadcast for the seven
parties under consideration here was just 195 (σ= 53). The word counts ranged from a low of 130 for
the Pirate Party and Alternative for Germany to a high of 269 for the SPD.6Each party is able to air their
election broadcast for free on the two public television networks, ZDF and ARD. The number of times that
each party can air their broadcast depends on their vote-share in the previous election and their status in the
parliament, with a minimum of two for any party eligible to compete in the elections. In addition, the largest
parties cannot have more than four times the number of election broadcasts as the smallest party. In 2013,
this meant that the two largest parties, the Christian Democrats and the Social Democrats, were able to air
their single broadcast eight times on both ZDF and ARD; the Free Democrats, the Greens, and the Left Party
were able to air their election broadcast four times on each network; and Alternative for Germany and the
Pirate Party were able to air their broadcast just twice on each network (Medienanstalten,2013).7Political
parties in Germany, unlike those in France, Portugal, Spain, and the United Kingdom, can also purchase air
time on commercial television. Typically, German parties run a shortened 30 −60 second version of the
same election broadcast that is aired on public television. Given their limited campaign budgets, German
parties do not invest heavily in ‘paid’ television advertising, preferring to focus their resources on putting
up campaign posters and billboards. The Kölner Stadt-Anzeiger estimates that the Social Democrats ran
their PEB 176 times on commercial television during the 2013 campaign and that the Christian Democrats
ran their PEB 140 times (Doemans,2013). Given the costs, smaller parties ran considerably fewer election
6Recall that the average number of words in the party manifestos used in our statistical analyses in the main test was 21,979.
7Party election broadcasts usually appear on television between 6pm and 11pm in the evening. The exact timing and sequence
of the party election broadcasts is determined randomly by the public television networks. Each election broadcast is introduced by
an official announcement to separate it from the normal broadcast content (Schweitzer,2008, 240).
14

broadcasts on commercial television.
Despite our misgivings about using party election broadcasts to examine the strategic use of emotive
language, we transcribed the 2013 PEBs of the CDU, the SPD, the FDP, the Greens, the Left Party, the
Pirate Party, and AfD, and ran them through the LIWC automatic sentiment analysis program.8The results
strongly support our hypotheses. In line with the Incumbent Party Hypothesis, the level of positive sentiment
employed by incumbent parties in their election broadcasts (5.1%) is almost three times higher than that
employed by opposition parties (1.76%). In line with our Prime Ministerial Party Hypothesis, the level of
positive sentiment employed by the prime ministerial party (5.82%) is one third higher than that employed
by its coalition partner (4.37%), and the level of positive sentiment employed by the non-prime ministerial
incumbent party is more than twice that employed by opposition parties. Finally, in line with our Extreme
Ideology Hypothesis, the level of positive sentiment employed by mainstream parties (3.64%) is 80% higher
than that employed by the more ideologically extreme parties (2.02%).
Party Websites
Internet campaigning provides parties with an opportunity to circumvent the filters of traditional media
outlets and directly present their messages to voters. It also provides parties with an opportunity to try
to shape how the traditional media outlets portray them. In this sense, internet campaign messages offer
a potentially useful insight into the strategic decisions of political parties regarding campaign sentiment.
However, there are a number of limitations associated with using internet campaign messages in this regard,
particularly relative to using party manifestos. The first has to do with the novelty and rapidly evolving
nature of internet campaigning. A consequence is that we have very few national-level elections, particularly
in Europe, in which internet campaign messages have played a significant role. One can increase the number
of available observations by examining individual party candidates (Zittel,2009,2015), but the focus here is
on political parties acting at the national level. A second limitation is that there is significant variation, both
across countries and within countries, with respect to the extent to which parties use tools such as websites
and social media, even in their more recent election campaigns (Gibson,2004;Gibson and Römmele,2009;
Obholzer and Daniel,2016). A more practical limitation is that many uses of social media, such as Tweets,
involve few words, making it difficult for automatic sentiment analysis tools to reliably capture the emotive
content of individual messages.
8Each of the party election broadcasts can be viewed online here.
15

Despite these limitations, we now briefly examine the use of internet campaigning in Germany, and
in particular, party websites during the 2013 federal elections. National parties in Germany began to develop
their online presence in the mid-1990s. However, it was not until the 2002 elections that Germany had its
“first professional online campaign” (Schweitzer,2008, 242). Only in the 2009 elections, following the
widely publicized success of Obama’s internet campaign in the United States in 2008, did German parties
begin to incorporate web 2.0 tools, such as blogs, Twitter, and Facebook, into their online election campaigns
(Jungherr,2015). Digital tools were further integrated into party campaign strategies in the lead-up to the
2013 elections. The extent to which internet campaigning has been adopted and exactly how digital tools
are used varies across different political parties (Jungherr,2016).
Despite the increased availability and use of digital tools, there is a strong consensus that these meth-
ods have not fundamentally changed the traditional style of German election campaigns, which continues
to focus on billboards, press coverage, and televised campaigning.9In effect, internet campaigning is con-
sidered supplemental, rather than central, to the election campaigns of German parties. Consumption of
internet campaigning in Germany also remains relatively low compared to the consumption of political
news via more traditional media outlets. In the two months prior to the 2013 elections, for example, 60%
of Germans used local and regional newspapers to keep abreast of the election campaign and 80% watched
political developments on one of the two main public networks, ARD and ZDF. In contrast, only 10% of
Germans claimed to follow the election campaign via social networking sites such as Facebook or Twitter
(Partheymüller and Schäfer,2013). The impact of internet campaigning on election outcomes has also been
challenged. For instance, there is little evidence that internet campaigning is related to election outcomes at
the federal, regional, or local levels in Germany (Marcinkowski and Metag,2013). Some studies, though,
suggest that internet campaigning in Germany can help mobilize voters indirectly by increasing media at-
tention and by shaping media narratives (Flemming, Metag and Marcinkowski,2013;Jungherr,2016).
Drawing on in-depth interviews with key campaign personnel, Jungherr (2016) finds that websites
were central to, and the most visible elements in, the online campaigns of German parties during the 2013
elections. His conclusion that “websites came to mirror the central narrative of each campaign” (365) is not
surprising given that campaign personnel at the time saw no distinction between their traditional election
campaign tactics and their online activity. Given this, we now use party websites to examine the strategic
9This was the conclusion reached by analyses of internet campaigning in the 2002 and 2005 elections (Schweitzer,2008), as
well as the more recent 2009 (Jungherr,2015) and 2013 (Jungherr,2016) elections.
16

use of emotive language in the internet campaigning of German parties. As German election campaigns are
short, with much of the active campaigning occurring in the last few weeks, we chose to examine German
party websites during the last four weeks of the 2013 election campaign.10
Before presenting our results, there are several things to note about our analysis of German party
websites. The first is that our emphasis on the text found on party websites means that we are ignoring how
the use of images and videos can engender particular emotions and shape campaign sentiment. This is quite
pertinent as the CDU provided a large number of Youtube videos on its website and the SPD frequently used
short video clips to highlight the activities of its party leader (Jungherr,2016, 370). The second is that the
websites sometimes contain interactive content, with the consequence that some of the archived text may
not come from the parties. The third thing to note is that any analysis of party websites has to decide how
much of the website to examine. How deep – how many mouse clicks from the homepage – should one go?
Should we include the material that is directly linked to from each website? The variation in the structure of
the different websites complicates these choices. Given our purposes here, we saw no principled theoretical
criteria for making these types of choices. To achieve some minimal degree of comparability across the
German party websites, we therefore decided to examine only the text that appeared on each party’s main
page about a month (August 24) before the election.11 The average number of words on a party’s main page
was 855, ranging from a low of 394 words for the Left Party page to a high of 1886 words for the SPD page.
On the whole, the results of our analysis of party websites are supportive of our hypotheses. In
line with our Incumbent Party Hypothesis, the level of positive sentiment employed by incumbent parties
(2.00%) is almost five times higher than that employed by opposition parties (0.42%). Contrary to our
Prime Ministerial Party Hypothesis, the level of positive sentiment employed by the prime ministerial party
(1.55%) is less than that employed by its coalition partner (2.44%). However, as predicted, both incumbent
parties exhibit more positive sentiment than each of the opposition parties. Finally, in line with our Ex-
treme Ideology Hypothesis, the level of positive sentiment employed by mainstream parties on their website
(1.30%) is over four times higher than that employed by the more ideologically extreme parties (0.30%).
10The websites were archived using GNU Wget (https://www.gnu.org/software/wget/). The raw .html files were then con-
verted into .txt files using pandoc (https://pandoc.org/). Finally, the .txt files were then run through the LIWC automatic
sentiment analysis program.
11The parties should have had enough time to tailor their webpages to their electoral campaigns by this date. There appears to
have been only marginal changes to the text found on the party main pages after this date.
17

Conclusion
In this brief case study of the 2013 German elections, we provided additional information to support our
argument in the main text. First, reanalyzing individual-level experimental data from the 2013 German Lon-
gitudinal Election Study (GLES), we presented evidence consistent with the literature’s claim that campaign
sentiment can influence how individuals evaluate the state of the world. Second, we examined the campaign
sentiment used in different types of campaign messages – party manifestos, televised election debates, party
election broadcasts, and party websites. In almost every case, the results of our analyses provided support
for our Incumbent Party Hypothesis, our Prime Ministerial Party Hypothesis, and our Extreme Ideology
Hypothesis. These particular results, when taken together, are consistent with our claim that the language
and campaign messages found in manifestos are repeated when parties “communicate to the public via other
avenues, such as campaign advertisements, party elites’ campaign speeches, and media interviews” (Adams,
Ezrow and Somer-Topcu,2011, 372).
18

Online Appendix E: Figures using Two-Tailed 90% Confidence Intervals
Figures 4through 7in the main text provide information with which one can evaluate our hypotheses. In
all four figures, we employed two-tailed 95% confidence intervals. For those who are interested, we now
provide equivalent figures with two-tailed 90% confidence intervals. Our inferences remain unaffected, and
the only difference is that the confidence intervals are now slightly smaller.
Figure 9: Positive Sentiment and a Party’s Incumbency Status (90% Confidence Interval)
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
Positive Sentiment
Opposition Party Non-PM Incumbent Party PM Incumbent Party
Note: Figure 9plots the predicted level of Positive Sentiment for opposition parties, non-prime ministerial incumbent parties, and prime ministerial
incumbent parties using the results from Model 2 in Table 2. The solid blue lines represent two-tailed 90% confidence intervals.
19

Figure 10: Positive Sentiment and a Party’s Left-Right Policy Position (90% Confidence Interval)
.4
.6
.8
1
1.2
1.4
1.6
1.8
2
2.2
Positive Sentiment
0
5
10
15
20
Percentage of Observations
0 1 2 3 4 5 6 7 8 9 10
Left-Right Position
Note: The solid black line plots the predicted level of Positive Sentiment for opposition parties across the left-right policy space using the results
from Model 3 in Table 2. The dashed blue lines represent two-tailed 90% confidence intervals. The black vertical axis on the left represents the
predicted value of Positive Sentiment. The light gray vertical axis on the right pertains to the histogram and indicates the percentage of observations
in the sample at different values of Left-Right.
Figure 11: The Effect of Objective Economic Indicators on Positive Sentiment conditional on Incumbency
Status (90% Confidence Intervals)
-.4
-.3
-.2
-.1
0
.1
.2
Effect of Inflation on Positive Sentiment
Opposition Party Incumbent Party
(a) Inflation
-.3
-.2
-.1
0
Effect of Unemployment on Positive Sentiment
Opposition Party Incumbent Party
(b) Unemployment
Note: Figure 11 shows the effect of objective economic indicators on Positive Sentiment. Panel (a) shows the effect of a one standard deviation
increase in inflation on Positive Sentiment for opposition and incumbent parties using the results from Model 8 in Table 2. Panel (b) shows the effect
of a one standard deviation increase in unemployment on Positive Sentiment for opposition and incumbent parties using the results from Model 9 in
Table 2. The solid blue lines represent two-tailed 90% confidence intervals. The coefficient on Incumbent Party ×Inflation is 0.04 (0.02), while
the coefficient on Incumbent Party ×Unemployment is −0.01 (0.02); standard errors are shown in parentheses.
20

Figure 12: The Effect of Incumbency Status on Positive Sentiment conditional on Inflation (90% Confidence
Intervals)
-.5
0
.5
1
1.5
2
Effect of Incumbency on Positive Sentiment
0
5
10
15
20
25
30
35
Percentage of Inflation Observations
0 5 10 15 20 25 30
Inflation
Note: The solid black line in Figure 12 shows the effect of being the incumbent prime ministerial party on Positive Sentiment across the observed
range of inflation using the results from Model 8 in Table 2. The dashed blue lines represent two-tailed 90% confidence intervals. The black vertical
axis on the left indicates the magnitude of the effect of being the incumbent prime ministerial party. The light gray vertical axis on the right pertains
to the histogram and indicates the percentage of observations in the sample at different values of Inflation.
21

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