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Popularity cues in online media: Theoretical and
methodological perspectives
Popularitätshinweise in Online-Medien: Theoretische und
methodologische Perspektiven
Pablo Porten-Cheé, Jörg Haßler, Pablo Jost, Christiane Eilders & Marcus Maurer
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Studies in Communication and MediaStudies in Communication and Media
Pablo Porten-Cheé (Dr.), Weizenbaum Institute for the Networked Society, Berlin, Freie Uni-
versität Berlin, Hardenbergstrasse 32, 10623 Berlin, Germany; Contact: p.porten-chee(at)
fu-berlin.de
Jörg Haßler (Dr.), Institut für Publizistik, Johannes Gutenberg-Universität Mainz, Jakob-
Welder-Weg 12, 55128 Mainz, Germany; Contact: joerg.hassler(at)uni-mainz.de
Pablo Jost (M.A.), Institut für Publizistik, Johannes Gutenberg-Universität Mainz, Jakob-
Welder-Weg 12, 55128 Mainz, Germany; Contact: pablo.jost(at)uni-mainz.de
Christiane Eilders (Prof. Dr.), Institute of Social Science, Communication and Media Studies,
Heinrich Heine University Düsseldorf, Universitätsstrasse 1, 40225 Düsseldorf, Germany;
Contact: christiane.eilders(at)phil.uni-duesseldorf.de
Marcus Maurer (Prof. Dr.), Institut für Publizistik, Johannes Gutenberg-Universität Mainz,
Jakob-Welder-Weg 12, 55128 Mainz, Germany; Contact: mmaurer(at)uni-mainz.de
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Popularity cues in online media: Theoretical and methodological
perspectives
Popularitätshinweise in Online-Medien: Theoretische und
methodologische Perspektiven
Pablo Porten-Cheé, Jörg Haßler, Pablo Jost, Christiane Eilders & Marcus Maurer
Abstract: Popularity cues, such as likes and shares, point to mainly positive user reactions.
On an aggregated level, they either indicate relevance assignments or endorsements of on-
line items, particularly in the context of political communication. Second, popularity cues
may affect the audience’s political perceptions, behaviors, and attitudes. This paper addresses
theoretical and methodological issues for both perspectives. Drawing on concepts such as per-
ceived relevance, attitudinal consonance, and persuasion, the antecedents of liking and sharing
are discussed. Then, the effects of popularity cues are described, mainly against the backdrop of
the spiral of silence theory and heuristic processing. The degree of elaboration is identied as a
key factor for understanding why political content is liked or shared and how Likes and Shares
render political effects on an individual level. Methodological issues concerning data collection
as well as the validity and viability of studies on popularity cues are discussed.
Keywords: Popularity cues, liking, sharing, social media, political communication, media
effects
Zusammenfassung: Popularitätshinweise wie Likes und Shares signalisieren grundsätzlich
positive Nutzerreaktionen. Im Kontext politischer Kommunikation sind sie in ihrer aggre-
gierten Form entweder Indikator für Relevanzzuweisungen von oder die Zustimmung zu
Online-Beiträgen. Popularitätshinweise können aber auch Faktoren sein, welche die Wahr-
nehmung, das Verhalten und die Einstellungen des Publikums beeinussen. Dieser Beitrag
thematisiert theoretische und methodologische Aspekte für beide Perspektiven. Im Rück-
griff auf Konzepte wie wahrgenommene Relevanz, Einstellungskonsonanz und Persuasion,
werden zuerst die Gründe für das Liken und Sharen diskutiert. Danach wird die Wirkung
von Popularitätshinweisen hauptsächlich vor dem Hintergrund der Schweigespiraltheorie
und heuristischer Informationsverarbeitung erörtert. Die Informationsverarbeitung wird
als Schlüsselfaktor identiziert um zu verstehen, wie das Liken und Sharen politischer In-
halte entsteht und welche politischen Effekte Popularitätshinweise auf Individualebene
hervorrufen. Die methodologische Diskussion bezieht sich auf Fragen der Datenerhebung,
sowie der Validität und der Durchführbarkeit von Studien zu Popularitätshinweisen.
Schlagwörter: Popularitätshinweise, Liking, Sharing, Soziale Medien, politische Kommuni-
kation, Medienwirkung
Popularity cues in online media (Perspectives)
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Note: This research was supported by the German Research Foundation [research
group “Political Communication in the Online World”, subprojects 2 and 4, grant
number 1381].
1. Introduction
A great deal of the expected societal and political consequences of evolving online
media stems from the suspicion that these follow other logics than media in the
traditional sense. Popularity cues, as represented by Likes and Shares, are online
phenomena that are part of such kinds of genuine online logic. Popularity cues
are drivers of what Webster (2011) recently conceptualized as “privileging popu-
larity” in the online world, which means that online, popular content is privileged
over unpopular content. This applies to both the supply and demand sides. On
the one hand, communicators thoroughly monitor their published items and pro-
mote those that have been the most popular among the users (Singer, 2014). On
the other hand, when forming their opinions, users are certainly overwhelmed by
the multitude of online items that present different perspectives. Then, users may
form their opinions based on online items that were previously liked by their
peers and could be encouraged to share these items, just as the privileging popu-
larity paradigm predicts. Thus, political actors, such as parties, candidates, or
other political campaigners, may conclude that their political messages online
should reach as many Likes and Shares as possible to have the intended impact,
often involving of setting one’s own agenda, or, most archetypically, to persuade.
In campaigns, when political debates often get controversial and the tone often
rough, informed suspicions have been voiced that the visible popularity of politi-
cal messages online is manipulated applying software-driven social bots (e.g.,
Woolley, 2016). While a robust empirical analysis on the effect of social bots on
the production of visible popularity is still needed, the potential problem for po-
litical communication is evident: A reasoned public discourse (Habermas, 2006)
under the conditions of publicly uttered opinions that pretend to be supported by
many fellows impedes the citizens from learning how strongly the public backs
certain political positions, and thus also prevents the citizens from receiving a
valid repertoire of opinions from which oneself can deliberatively form one.
On one hand, Likes and Shares may be subject of manipulation – with poten-
tially severe harm to the public sphere. On the other hand, however, they most
likely provide some degree of orientation when forming personal opinions. This
ambivalence points to the need to look behind the Likes and Shares and untangle
why we visibly support political content online and how political content visibly
supported by others affects the citizens’ political attitudes and behaviors.
In a broad sense, Likes and Shares were conceptualized as popularity cues that
represent metric information about previous users’ behavior or their evaluations
of entities (see Haim, Kümpel, & Brosius’ denition in this issue). Popularity cues
may have different labels across different platforms. For the purpose of this pa-
per, Likes, Shares, and other metric cues are narrowly dened as popularity cues
that primarily point to user reactions that might either indicate attention and
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relevance assignment to social media messages or online media items or indicate
support and endorsement.
The aim of the paper is to specify the role of popularity cues in social media
messages or online media items in the realm of political communication research.
To investigate the factors inducing liking or sharing and the effects these cues have,
different theoretical approaches and empirical evidence from various strands of
research dealing with issues and actors of the political sphere are discussed. The
paper is divided into two main sections: Popularity cues are rst discussed as de-
pendent variables and secondly as independent variables in media selection and
effects research in the eld of political communication. The discussions result in
two analytical perspectives. From the rst perspective, popularity cues are con-
ceptualized as metric outcomes on the individual level indicating relevance
assessments, attitudinal consonance, and persuasion (see section 2.1). However,
popularity cues are “cues” only for the subsequent users. Seen from this second
perspective, popularity cues are understood as causes for a variety of outcomes,
such as media selection, or perceptual and cognitive effects (see section 2.2).
Moreover, the paper provides a critical review of the methods applied to study-
ing the causes for liking and sharing (see section 3.1) and the effects of popularity
cues (see section 3.2), pointing out possible pitfalls and potentials for further re-
search. In this paper, popularity cues are considered in two contexts of media re-
ception: rst, within online media items, and second, social media messages. The
latter can be regarded as spaces where popularity cues are typical outcomes of
political messages that may inuence their potential effects. However, because
Likes and Shares of social media messages compete with additional social cues
that could inuence why individuals apply popularity cues and whether they are
affected by them, different contexts of reception were considered whenever ap-
propriate.
2. Theoretical approaches to popularity cues
2.1 Popularity cues as dependent variables
Why do we like, and why do we share political content? The answers to these
questions are in the center of this section. This starts with a discussion of what
users have in mind when they apply popularity cues and elaborates on the com-
monalities and differences between liking and sharing (for the related concept of
external relevance cues designated by users, see Haim, Kümpel, & Brosius’ relat-
ed discussion in this issue). While both are mainly positive reactions toward po-
litical messages, they may be understood as products of different amounts of cog-
nitive evaluation. The discussion then goes on, highlighting some key message
features (e.g., formal features, such as the use of links or photos, and content ele-
ments, such as the use of different rhetorical strategies) that predict the number of
Likes and Shares of political messages. These reviews shall provide insights into
the meanings of Likes and Shares by drawing conclusions from onliners’ liking
and sharing behavior. In addition, we show how to make use of the number of
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Likes and Shares as non-reactive information about citizens’ attitudes and behav
-
ior in political communication research.
2.1.1 Functions of popularity cues
The Like button is established and frequently used “to express a variety of affec-
tive responses such as excitement, agreement, compassion, understanding, but
also ironic and parodist liking” (Gerlitz & Helmond, 2013, p. 1358). Whereas the
most attributed meaning of a Like seems to be an expression of a positive attitude
toward the message, the two last-mentioned examples seem to be negative. Re-
viewing empirical literature might help to paint a clearer picture. In in-depth in-
terviews, Gao (2016) distinguished between referential and expressive motives of
liking. Whereas “liking the content” is the most reported referential motive to like
a post, liking to show other users “having read” the article is a less relevant mo-
tive. The most reported expressive reasons for liking a post are agreeing with the
author (e.g., sharing the same attitude), appreciating the mood, or sharing the
same interests. Other studies employing focus groups and semi-structured inter-
views identied the positive evaluation of content or the posters’ behavior as
strong motives for liking content on Facebook as well (e.g., Hayes, Carr, &
Wohn, 2016). Brandtzaeg and Haugstveit (2014) found different reasons for lik-
ing on Facebook; users reported liking posts because they feel socially responsi-
ble, emotionally attached, or because they want to present themselves as respon
-
sible. Moreover, a minority of users tend to like because the costs are low and
liking is a routinized behavior. De Vries, Gensler, and Leeang (2012) asked
whether the valence of the message inuences the willingness to like or to com-
ment on brands’ posts on SNSs. Users tend to comment on negative or positive
brand posts to the same extent, but liking is positively related to the valence of
the post. Twitter offers users the same option: Likes “are commonly used to show
appreciation for a Tweet” (Twitter, 2016). An investigation of the motives of lik-
ing Tweets showed that users like Tweets because they actually like the content of
the Tweet (Meier, Elsweiler, & Wilson, 2014).
By introducing the Like button, Facebook aimed to offer “an easy way to let
people know that you enjoy it without leaving a comment” (Facebook, 2016).
Summarizing the ndings, we argue that the function of Likes is to indicate the
endorsement of a message’s content. In political communication, the number of
Likes seems to be an applicable indicator to assess the degree of public appeal of
political positions online. From the individual point of view, liking a certain politi-
cal position expressed in an online item may present a low-threshold way to
change public opinion, rst because one knows that one’s sole “Like” adds to pos-
sibly many others and second, each additional like may lower the others’ restraints
to support certain opinions as well—changing public opinion on the user-level.
Recent studies have identied several motives of sharing online content. Ac-
cording to a meta-analysis by Kümpel, Karnowski, and Keyling (2015), these mo-
tivations are self-serving, altruistic, and social motives. Lee and Ma (2012) found
that users share content to get in touch with other users, to store information,
and to enhance their own reputation. Oh and Syn (2015) showed that reputation,
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reciprocity, and community interest correlate strongly. For that reason, it is plau-
sible that users, when sharing content, are looking for the interests of others as
well. Bobkowski (2015) found that users share news they perceive as relevant for
themselves as well as for their peers, thereby relying on the perceived consequenc-
es, the likelihood that news will affect the users and their peers, and their imme-
diacy. Other researchers have found that users are more likely to share news in
line with their own attitudes or reecting their own views and experiences (Choi
2016), rather than sharing messages that oppose their own political beliefs (An,
Quercia, & Crowcroft, 2013). However, users also share content from ideologi-
cally biased news outlets: Because online peers tend to be similar in socio-demo-
graphic and political attitudes, sharing content in line with their own beliefs
seems to be a logical consequence if users want to increase their reputation by
sharing online content. Concerning Twitter, Boehmer and Tandoc (2015) found
that users’ interest in the topic, perceived relevance for followers, and expressed
opinions in line with their own attitudes are predictors of Retweets as well.
With the Share button, Facebook gives users the opportunity to spread content
in their personal network. We conclude that the function of Shares on Facebook
or Twitter is to indicate the relevance users attribute to a message. Given the em-
pirical insights, the number of shares may point to how important political issues
in online messages were considered by previous users. In this sense, to share not
only means to highlight an item, but also to gradually change what political is-
sues fellow users perceive to be important on a visible micro-level.
Regarding the underlying motives, liking and sharing both seem to be mainly
positive reactions toward a (political) message but might be a product of different
amounts of cognitive evaluation. This assumption can be explained by at least two
different mechanisms. First, compared to a simple Like, which is one among many
and only visible under the liked post, sharing content leaves visible traces on users’
own timeline, where other users can see the post and might criticize the author.
Referring to the fear of social isolation (Noelle-Neumann, 1993), studies show
that group conformity effects can reduce the willingness to post content in public
(Lee & Nass, 2002). In comparison to liking any content, users might elaborate
the messages deeper before sharing them because they want to prove whether the
message is in line with the opinion climate. Further, the effects of the fear of social
isolation can be equalized if people are certain about their point of view (Matthes,
Morrison, & Schemer, 2010), which is strongly predicted by the amount of cogni-
tive elaboration (Smith, Fabrigar, MacDougall, & Wiesenthal, 2008).
Second, as stated above, the motives of liking and sharing differ. Liking is
mainly a result of a positive evaluation of the message. The main motive of shar-
ing content seems to be the perceived relevance for the peer group. Whereas
strong attitudes toward an issue might end in biased processing, its perceived rel-
evance is positively related to users’ involvement, which might result in more in-
depth elaboration (Petty & Cacioppo, 1986). This again leads to the conclusion
that, compared to liking, sharing a post seems to be a result of a process of higher
elaboration. This preliminary conclusion is a case of how popularity cues research
can benet from a recipient-oriented perspective (see the call for such an ap-
proach by Haim, Kümpel, & Brosius in this issue).
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2.1.2 Effects of media content on popularity cues
Political communication research often involves surveys or experiments to ex-
plore the effects of political messages (exposure to hard news, campaign media,
etc.) on recipients’ attitudes and behaviors. In both cases, research might suffer
from using reactive methods. In surveys, respondents sometimes give answers that
are socially desirable (Presser, 1990). In experiments, subjects could guess the aim
of the study and intentionally give answers that support or disprove the hypo-
theses. Therefore, several researchers have recently attempted to replace surveys
and experiments with the use of non-reactive online analyses (e.g., Scharkow &
Vogelgesang, 2011).
As stated above, aggregated popularity cues could serve as indicators for both
the positive evaluation and perceived relevance of a message. Political communi-
cation literature indicates that various message features inuence the attitudes
toward political messages (e.g., Maurer & Reinemann, 2016). Therefore, these
features should have a positive effect on the number of Likes and Shares a mes-
sage gets. Statistically, these message features (independent variables) should ex-
plain the variance in the amount of popularity cues (dependent variables). In the
following section, possible perspectives in political communication are outlined
that might benet from using popularity cues as dependent variables in research
designs, as there is research on news factors, political persuasion, and visual po-
litical communication.
Since social media have become a relevant part of online news distribution and
consumption (e.g., Mitchell & Page, 2013, 2014), the selection processes of jour-
nalists and recipients work similarly, as they both rely on news factors while se-
lecting news for distribution or consumption. Whereas news factors are part of the
journalistic routine, they also guide users and determine their retention of news
(Eilders, 2006). Studies show a signicant positive relation between several news
factors and the perceived relevance of news stories (e.g., Weber & Wirth, 2013) or
a positive effect on both the selection and recall of news (Eilders, 2006). Populari-
ty cues allow researchers to investigate which attributes of messages enhance the
potential of getting shared and might deepen our understanding of the role news
factors play for audiences of political content online. In that case, the number of
Shares might be a proper indicator for the perceived relevance of news, and conse-
quently, political issues at stake. In this respect, non-experimental ndings suggest
that news factors, such as personalization and negativism, enhance the tendency to
share news articles with one’s Facebook friends (Haßler, Jost, & Maurer, 2016).
A prominent eld of political communication deals with the persuasive effects
of communication strategies. For instance, attacking one’s political opponent (e.g.,
Lau, Sigelman, & Rovner, 2007), using evidence (e.g., Reinard, 1988), or strategic
ambiguity (e.g., Aragones & Neeman, 2000) seem to be successful strategies to
form new, strengthen, or even change existing attitudes. In the context of persua-
sion research, both Likes and Shares might be suitable indicators to investigate the
amount of endorsement or support. Analyzing the 100 most-retweeted Tweets in
the 2009 German National Election, Jungherr (2014) found that personalization
and contest in campaign messages increase the number of Retweets. Bader et al.
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(2016) found that Tweets including evidence and two-sided arguments were more
often retweeted than those lacking such presentation characteristics. Empirical
ndings also support the assumption that Shares result from a process of deeper
elaboration than Likes, as users tend to share posts of politicians more often if
they contain strong arguments including evidence and strategic ambiguity, whereas
liking content is merely determined by peripheral cues, such as visual elements
(Jost & Maurer, 2016). However, whether individuals in fact engage with the con-
tent they share is disputed (Gabielkov, Ramachandran, Chaintreau, & Legout,
2016). Sharing is nevertheless plausibly linked with higher levels of elaboration,
but more empirical evidence is needed to support this assumption.
Finally, in the eld of visual communication, several experimental studies have
indicated that visual signals increase recipients’ attention toward a message (e.g.,
Graber, 1990). Moreover, visual signals contribute to political opinion formation,
especially in the case of politically uninvolved voters (Maurer & Reinemann,
2016). Consequently, the relevance of photos and videos for liking and sharing a
post can be used as an indicator for the importance of visual signals in the con-
text of social media. Hence, the vividness of a post, measured by visual elements,
has a positive effect on both liking and sharing on Facebook (De Vries et al.,
2012) and Twitter (Rogers, 2014). Future studies should also consider content
elements of photos and videos to investigate the role of, for example, gestures and
facial expressions for the likelihood of liking or sharing a post.
2.2 Popularity cues as independent variables
Popularity cues not only serve as expressions of appreciation or, in rare cases, even
the rejection of media content or specic formal features of a news item or social
media post. Since they are readily available in political messages online and easy to
grasp, they are also simple indicators of previous users’ reactions to a post. Thus,
they may consequently affect the political behaviors, cognitions, and attitudes of
the audience. Meanwhile, popularity cues may be the aggregate of valid user reac-
tions to political messages; however, as previously stated, social bots could cause
severe misrepresentations of aggregate popularity cues and harm public opinion
formation. Thus, political communication research has to untangle the mecha-
nisms behind the possible individual susceptibility to popularity cues. This section
therefore reviews approaches from media effects research suited to enhance our
understanding of how popularity cues inuence the audience in political terms.
2.2.1 Effects on exposure
Communication research has developed several theoretical approaches to explain
why users prefer specic types of media content (for an overview, see Hartmann,
2009). Motivational factors, cognitive factors on the users’ side, and media
characteristics have commonly gained the most attention. Regarding the latter
dimension, there is a wide strand of research on how presentation and formal
media characteristics affect news exposure (see e.g., Eilders, 2006). Knobloch-
Westerwick, Sharma, Hansen, and Alter (2005) addressed challenges for online
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media in emphasizing relevant content. Especially when legacy media items are
embedded in social media platforms, relevant news items are no longer indicated
by their position on the rst page or in rst place in TV or radio news. Instead,
popularity cues next to mass media items in social media now serve as sources to
infer the relevance of a news item. But why should individuals follow such cues?
One point of departure is the spiral of silence theory (Noelle-Neumann, 1993).
According to this approach, people monitor their social environment for cues
about public opinion on controversial political issues. It is assumed they do so
because they want to avoid situations of expressing opinions that deviate from
the predominant opinion. People hence need information to get an idea about the
public opinion. For most people, media represent an important part of the social
environment. They are easily available sources in gathering information about
what other people think.
In online media, news items that have received a great deal of user reactions
draw particular attention from consecutive users (e.g., Messing & Westwood,
2014). People could thus infer that the opinions in such popular news items re-
ect the opinions of the majority. To prevent social isolation, people are likely to
expose themselves to such news items, trying not to miss new and popular cues
on the alleged majority opinion. Thus, if an online item is popular – that is, liked
by many users – the item could be seen as reecting the opinion of many others,
or even the public. Following spiral of silence theory, as a consequence, individu-
als would then select the item because they want to know which opinion is en-
dorsed by the public. Seeing many Likes next to political news items will very
likely attract attention and induce the respective selection by individuals sensitive
to what other people think, even if they do not support the opinions on political
issues presented in those news items.
While the assumed popularity of opinions according to online news items can
only be assessed with regard to the size of the audience, the users do not necessar-
ily consider this relation in their assessment of an item’s popularity. However, al-
leged popularity may stimulate exposure to the items emphasized through popu-
larity cues. The explanation ties in with psychological approaches from media use
and effects research that have contributed to better understand the processing of
political information, such as need for orientation (Matthes, 2006). Individuals
with a high need for orientation are expected to be satised when they can select
content previously judged by their co-audience as relevant or worthy of support
because they can use such content to reduce their uncertainty about issues in
which they are strongly involved. Popularity cues reveal collective behavior, that
is, the selection of content. This visible behavior points to acceptable online news
that are helpful to guide one’s own opinions on often abstract and complex pub-
lic affairs and are thus worthy to select and adapt—in a manner known as the
bandwagon effect (Sundar & Nass, 2001). Research shows that individuals’ ex-
posure to online news is promoted by visible popularity cues (Knobloch-Wester-
wick et al., 2005) and that they opt for online news with many popularity cues
over others without such cues (e.g., Messing & Westwood, 2014).
Moreover, popularity cues provide information that might help in assessing
whether other audience members’ relevance assignments correspond with one’s
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owns. In the case of correspondence—that is, if one observes that subjectively
relevant political content is shared by many users—such social comparisons (Cor-
coran, Crusius, & Mussweiler, 2011) may foster exposure patterns because many
other users would afrm one’s behavior. If, however, media users have not devel-
oped robust relevance assignments, comparing themselves with others cannot
guide exposure. Popularity cues can nevertheless facilitate the decision to read or
watch a specic item on political issues because they point to popular content
that might be worth noticing.
2.2.2 Effects on perceptions and attitudes
Recently, communication researchers have begun to focus on socially and politi-
cally relevant perceptional and attitudinal consequences of encountering popular-
ity cues. These inquiries particularly concern the effects of popularity cues that
endorse the valence of posts or media items, such as Likes, on personal opinions
and the perception of public opinion. However, to date, there is no coherent and
convincing theoretical rationale explaining the effects.
Empirical evidence regarding the effects of Likes on perceptions and attitudes
is mixed: Oh (2014) found that most-liked user comments affected perceived
public opinion on presidential candidates in the direction of the comments’ va-
lence more strongly than comments without Likes. Jin, Phua, and Lee (2015)
found that the number of Likes on Facebook breastfeeding pages promoted posi-
tive attitudes toward breastfeeding – a topic that strongly refers to the denition
of social norms and may lead to political debates. In contrast, Lee and Jang’s
(2010) and Peter, Rossmann, and Keyling’s (2014) data showed that other users’
Likes next to online media items did not change public opinion perception on is-
sues of social relevance.
Users show a preference for media items or posts with many Likes or Shares
because they help to assess what political opinion the majority is likely to sup-
port—at rst sight. Such information is necessary and worth selecting to deter-
mine whether one could fear social isolation when expressing positions not sup-
ported by many others. Popularity cues thus serve as proxies for public opinion
and consequently shape its perception. This possible explanation, driven by the
spiral of silence approach, applies to perception effects as well as attitudes. Form-
ing personal opinions may be subject to the same mechanism: Users adopt opin-
ions they assume to represent public opinion.
Next to social conformity as a driving force for being susceptible to popularity
cues, individual information processing can further explain popularity cues’ ef-
fects. First, previously developed pre-attitudes certainly lower the tendency to
conform to the opinion apparently supported by others. A second theoretical
point of departure is the anchoring heuristic. When asked for estimations about
unknown issues, people pay attention to anchors, that is, information that ap-
pears rst (Tversky & Kahneman, 1974). Popularity cues may serve as such an-
chors; they often appear next to the titles of online media items at the beginning.
Regarding public opinion perception, the anchor heuristic could consist as fol-
lows: Likes at the beginning of online items are received as guiding cues to assess
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how the public’s endorsement regarding certain issue positions looks like, espe-
cially when previous knowledge on these issues is low. Aggregate popularity cues,
to a certain degree, function as easy-to-process statistics about public opinion,
such as prominently placed survey results in media items that present strong cues
for public opinion (Zerback, Koch, & Krämer, 2015). When previous perceptions
of public and personal opinions on political and social issues are lacking, rst-
place popularity cues can be convenient to develop preliminary perceptions and
opinions on political issues.
2.2.3 Boundary conditions of popularity cues’ effects
Personal factors and further media content characteristics may intervene in the
relations between popularity cues and exposure to media items, or between popu
-
larity cues and perceived public or personal opinion on political issues. Following
Lee and Jang (2010), the type of information processing is the key factor (also see
section 2.1.1). Dual process theories suggest a differentiation between central and
peripheral information processing (e.g., Petty & Cacioppo, 1986). On one hand,
the central route is associated with high levels of involvement or need for cogni-
tion (Cacioppo & Petty, 1982). It leads to searching for relevant verbal content
and arguments when scanning political media messages. On the other hand, the
peripheral route, which is associated with low degrees of issue involvement or
need for cognition, leads to a more random-type media use with fewer expecta-
tions in mind.
Hence, even if people look for political information online to assess public
opinion, peripheral processing makes them less attentive to media’s verbal con-
tent than to media features that facilitate cognitive access. Peripheral processing,
in turn, make users more susceptible to popularity cues that emphasize the items’
relevance. After selecting media items with these features, individuals are likely to
apply a heuristic to catch a message or opinion. Users could rely on popularity
cues to quickly understand the importance of positions on often complex political
issues depicted in media items. In consequence, personal opinion and perception
of public opinion may be affected in the direction supported by popularity cues.
At the same time, familiarity could intensify popularity cues’ effects: The more
people get used to specic media outlets, the more they develop conceptions of
their co-audiences (Hartmann & Dohle, 2005). This concerns information on the
positions the co-audiences usually take and whether these positions can be gener-
alized to the public in total or remain audience-specic.
A rm personal opinion will most likely prevent people from adopting differ-
ent opinions, even if they were backed by 1,000 Likes. In such a case, public
opinion perception will also hardly depend on aggregate cues expressing endorse-
ment for certain public opinions but be more strongly inuenced by projecting
one’s own opinions on public opinion perception (Fields & Schuman, 1976). Fur-
ther, need for distinction (Brewer, 1991) and seeking uniqueness (Snyder & From-
kin, 1980) may impede popularity cues’ effects. People striving to be different
than others may resist selecting media items many others have previously read or
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seen (Knobloch-Westerwick et al., 2005). They may also be hesitant to adopt the
opinions endorsed or to accept them as public opinions.
There are several other media characteristics that compete with popularity
cues affecting media selection. First and foremost, news factors (Eilders, 2006),
such as conict or unexpectedness and humor (Keyling, Kümpel, & Brosius,
2015), catch the online audience’s attention and prevent it from being susceptible
to popularity cues’ effects. Finally, context matters: People may consider popular-
ity cues regarding opinions on issues depicted in the media, especially if the issues
are controversial, as it is particularly important to know the public opinion in
such cases.
3. Methodological approaches to popularity cues
After providing a theoretical discussion on the functions, conditions, and possible
effects of popularity cues around the communication of political issues and ac-
tors, this section is devoted to a critical methodological review of how popularity
cues research is conducted. The aim of this section is to engender a sensibility for
issues that appear in the collection and analysis of popularity cues in all areas of
communication research, including political communication research. Solutions
to such issues may be found in the latter eld as well as neighboring areas.
3.1 Popularity Cues as Dependent Variable
3.1.1 Technical challenges
When analyzing popularity cues, researchers face the same technical challenges as
when conducting content analyses of conventional websites (Haßler, Maurer, &
Holbach, 2014). Besides challenges such as dynamics, multimediality, hypertextu-
ality, and personalization, there are a few further difculties that need to be ad-
dressed when analyzing popularity cues.
First, researchers need to choose the right technical tools for data collection. To
date, a wide variety of instruments is available enabling the automated or semi-
automated storing of popularity cues (Gaffney & Puschmann, 2014). There are
two main kinds of such tools: The rst stores Likes, Shares, upvotes etc. via the
front-end by taking screen shots or crawling websites. The second uses the back-
end by storing information provided by the application programming interface
(API) of the SNS (Keyling & Jünger, 2016). On one hand, these tools offer the
advantage to store great amounts of information on popularity cues very quickly.
On the other hand, most APIs only provide meta or raw data. Thus, further tools
are necessary to analyze or to visualize these data. While most content informa-
tion about liked or shared articles is fully available via APIs, information about
graphic design and especially layout is not available via the back-end of SNS.
Therefore, the specic research question determines which tools should be used to
store information.
Second, researchers need to decide whether to analyze popularity cues from
original (e.g., journalistic or political) websites or from social media sites. On the
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one hand, research questions focusing on the characteristics enhancing the number
of Likes and Shares in social media can only be addressed when the exact formal
and content characteristics are measured. On the other hand, especially journalis-
tic websites are among the most far-reaching websites. As many provide aggregat-
ed popularity cues directly with their articles, this information can easily be stored
together for analyses (Haßler, Maurer, & Holbach, 2014). Storing all information
directly from (journalistic) websites has the advantage that a wide variety of ag-
gregated popularity indicators can be analyzed together with formal and content
characteristics of original articles. Thus, not only Likes and Shares on Facebook or
Tweets can be analyzed, but also the amount of upvotes, views, or comments.
Third, researchers need to choose the right interval of data collection against
the backdrop of their specic research questions. Regardless of the source from
where aggregated popularity indicators are stored, researchers need to decide
how often and how long aggregated popularity indicators are to be monitored to
answer the specic research questions. Storing all information on the article and
aggregated popularity cues under scrutiny at the same time seems to be the easiest
form of data collection. However, this harms the comparability of the amount of
popularity cues because the individual publication time affects how often an arti-
cle is liked or shared. Posts that were published hours ago might have attracted
more Likes than posts published only seconds ago. Thus, the time of publication
always needs to be considered when analyzing aggregated popularity cues (Cas-
tillo, El-Haddad, Pfeffer, & Stempeck, 2014). Furthermore, it is impossible to
measure the growth of popularity or trends when storing data only once. Thus,
long storage intervals offer advantages for answering questions on when and how
long articles are liked or shared.
3.1.2 Validity
As explained previously, knowing the factors inuencing the articulation of popu-
larity helps us to understand what makes sources and messages interesting or
even persuasive. To isolate the factors inuencing the articulation of popularity, it
is necessary to measure the popularity cues themselves as well as formal and con-
tent factors of the messages that are liked or shared. Therefore, the rst issue of
validity concerns strategies of data analysis. Generally, there are three basic ap-
proaches to analyze the factors inuencing Likes and Shares:
First, factors can be analyzed by focusing on messages that have generated
considerable amounts of Likes and Shares. For example, Jungherr (2014) ana-
lyzed features of the 100 most-retweeted Twitter messages. Although his analysis
offers useful insights into characteristics of popular tweets, his results do not in-
form about the characteristics of messages that inuence liking or sharing. The
analyzed characteristics could have been present in, for example, the 100 least-
retweeted messages as well. A second approach compares articles or posts that
contain certain factors and articles that lack these factors. Using this approach,
Bader et al. (2015) compared the mean values of Retweets of articles that used
statistical evidence, two-sided arguments, or irony as rhetorical devices and arti-
cles that did not use these rhetorical devices. Albeit the opportunity to compare
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the characteristics of popular as well as unpopular tweets, this bivariate approach
cannot be used to analyze more than one inuencing factor. To address the short-
comings of these approaches, third, multivariate analysis can be used to analyze
two or more factors that might simultaneously inuence the number of Likes or
Shares. Trilling, Tolochko, and Burscher (2017) used regression analyses to ana-
lyze the effects of various content criteria on the number of Likes and Shares
controlling for inuences of other content criteria (see also Haßler, Jost, Maurer,
2016). As this procedure clearly allows to identify the inuence of different mes-
sage elements on popularity cues, multivariate analysis is recommended.
A second issue of validity concerns the question of whether ndings from so-
cial media can be generalized. One formal factor that needs to be considered
when analyzing the success criteria of either Facebook pages or the number of
Likes of website articles is the popularity of the source itself. A Facebook page or
a website that has hundreds of thousands of Likes or followers will most likely
generate more Likes on single articles than a page with a total of, for example, 20
Likes. Another formal factor is the article placement on a website. For example,
articles placed on the top of websites are more likely to be shared – and liked –
than articles at the bottom (Berger & Milkman, 2012). Moreover, researchers
need to consider what the baseline regarding the amount of popularity cues is
and if the exact amounts of popularity cues can always be easily compared with
each other. There are websites that like their own articles soon after they share
them on Facebook. Moreover, many journalistic websites do not allow liking or
sharing for all their articles.
In addition, specic characteristics of SNS need to be taken into consideration
when generalizing the results from Likes, Shares, or Retweets to general attention
criteria or processes of persuasion. Trilling et al.’s (2016) results indicate that ei-
ther the Facebook algorithm or Facebook user habits favor different content cri-
teria than have been found for Twitter. As shown above, there might be a positiv-
ity bias favoring positive messages, as they are more “likeable” than negative ones
(see Reinecke & Trepte, 2014).
Finally, regarding generalizability, social media users’ socio-demographic fac-
tors must be taken into account. For example, they are younger than newspaper
audiences (Perrin, 2015). This, for example, raises the question of whether their
relevance criteria are different from those of other people. Therefore, researchers
not only need to choose between different analysis procedures, but also consider
characteristics of the communicator, the message, and the receiver when general-
izing results from analyses of factors inuencing Likes, Shares, and Retweets.
3.2 Popularity cues as independent variables
3.2.1 External Validity
The effects of popularity cues are usually studied in experimental designs where
the effects are isolated and other factors are controlled. Since the experiments aim
at a high degree of correspondence with real-world settings, popularity cues have
been placed prominently next to real (Messing & Westwood, 2014), but mostly
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ctitious (e.g., Jin et al., 2015; Peter et al., 2014) online news and information
items. Some ctitious experimental settings have been particularly realistic and
had external validity according to experts, for example, journalists (Oh, 2014).
Regarding political communication research, however, popularity cues on politi-
cal messages have rarely been tested. Given the potentially severe consequences of
being susceptible to Likes, further inquiry must be provided testing popularity
cues’ consequences on issues that relate to collective norms and interests.
While the layout of online media items is similar in most studies, the opera-
tional implementation of aggregate popularity cues is diverse. Some researchers
have used Facebook Likes (Jin et al., 2015; Messing & Westwood, 2014; Peter et
al., 2014) or generic forms of Likes (Lee & Jang, 2010; Oh, 2014), while others
have used generic content ratings (e.g., Knobloch-Westerwick et al., 2005). Inter-
estingly, the different operationalizations apparently do not correspond with sys-
tematic differences in the ndings reported in the previous section. However,
there are other problems related to the operationalization that remain to be
solved: Using the number of Likes as the stimulus, it is difcult to determine the
difference between many and few Likes in participants’ perceptions. This might
explain the variance in the ndings.
Another problem concerning external validity in this strand of research relates
to the competition between online media items. Under real-live conditions, expo-
sure to specic online media items depends not least on the other media items
available. In experimental settings, however, the online media item under scrutiny
is mostly presented separately from the larger context. To establish realistic con-
ditions for selective exposure, a great deal of effort (especially Messing & West-
wood, 2014) was put into creating online environments where individual media
items can be selected out of several other items. Although this elaborated ap-
proach deserves credit for meeting external validity criteria and needs to be con-
sidered in further research, it has sparked few similar studies.
3.2.2 Internal validity
Popularity cues in experiments can exert their effects when proper testing condi-
tions are fullled – that is, while keeping all other possible variations constant in
the experimental and the control conditions, popularity cues are included in the
experimental condition only. However, political communication research must
keep in mind that besides constructing clear manipulations, these must reect re-
al-world conditions to provide appropriate estimations. Obviously, there is cer-
tainly a clear difference in the effects of ve versus 500 Likes on a news item.
Most manipulation checks that have been applied show popularity cues to be re-
called or perceived as intended (Jin et al., 2015; Knobloch-Westerwick et al.,
2005; Lee & Jang, 2010). Nevertheless, even if manipulation checks are part of
the solution, they are also part of the problem when testing for internal validity.
The problem appears when participants are asked about their perception of pop-
ularity cues before dependent variables are measured. Then, the latter assessment
will most likely be affected by the fact that subjects know that popularity cues are
supposed to make a difference. The reverse case is unfortunately harmful as well:
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Asking about cognitions and perceptions rst may increase the sensitivity to later
conrm that numeric cues have been perceived. This is likely to take place when
subjects want to justify why their cognitions and perceptions have changed fol-
lowing stimulus exposure. Finally, manipulation checks are not helpful when they
measure a variable that is identical or too close to the dependent variable that is
presumed to be affected by popularity cues. In such cases, it is probably wiser to
justify internal validity with proper testing conditions.
4. Discussion
Today, popularity cues are widespread online phenomena that consist of gradu-
ally reected individual behaviors, but most recently also detrimental software-
driven manipulations. The online environment systematically privileges popular-
ity (Webster, 2011), and thus popularity cues appear there in a self-reinforcing
way: The more fellow users apply popularity cues to label political messages as
popular, the stronger political communicators promote the availability of such
messages online (Singer, 2014). Thus, it becomes more likely that certain political
messages receive further popularity cues by consecutive users – and multiply their
potential impact. Despite the questionable credibility of popularity cues (human-
or bot-caused), as social media have become more and more important in the
communication processes of news media, political actors, and political organiza-
tions, popularity cues, such as Likes and Shares, may also become more and more
important for the individual information orientation and political opinion forma-
tion. Consequently, several questions arise concerning popularity cues as either a
dependent or independent variable in the political communication process: (a)
Why do recipients like or share online political messages (functions of popularity
cues)? (b) Which message elements explain why some political messages or items
are frequently liked or shared, while others are not (success criteria of popularity
cues)? (c) Which politically relevant effects do popularity cues have on recipients
(effects of popularity cues)?
The theoretical considerations and empirical ndings discussed in this paper
suggest the following answers to these questions: Popularity cues are indicators of
the perceived relevance and the usually positive evaluation of news items and
political messages. Generally, Likes and Shares are indicators of both relevance
perception and evaluation. However, Shares seem to result from a more in-depth
elaboration process.
To examine which message elements enhance the popularity of a message, sev-
eral established theories in communication research can be consulted. For exam
-
ple, political messages that include persuasive elements or news factors are liked
and shared more often than messages without these elements. In turn, political
communication research could benet from analyzing the causes of the populari-
ty of social media messages, as they provide access to easily available and non-
reactive data. Finally, popularity cues can be used as independent variables in
several media effects theories. For example, concerning the spiral of silence theory
and heuristic processing, users may be attentive to rst-placed popularity cues
that can be easily grasped when monitoring the environment for information on
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public opinion. They serve as proxies for public opinion and shape public opinion
perception, especially under conditions involving the lack of personal opinion
and uncertainty. This paper only pointed to several feasible theoretical explana-
tions. Other approaches that are able to back up the susceptibility to popularity
cues are necessary for further theory building.
The analysis of popularity cues is also subject to several methodological chal-
lenges: The rst concerns questions of data collection, for example, how the large
amounts of messages and the frequently changing amounts of popularity cues to
these messages can be stored. Second, the question arises of whether data exclu-
sively involving the group of social media users can be generalized to the total
media audience, for example, when the effects of persuasive message elements or
the spiral of silence theory are under examination. Third, applying ctitious me
-
dia items limits external validity when testing for popularity cues’ effects. Run-
ning manipulation checks may be one way to test for the internal validity of
popularity cues; however, they go hand in hand with several limitations. In gen-
eral, an appropriate test design is key to assume that participants may be suscep-
tible to popularity cues’ effects. Finally, how many Likes are considered an indica-
tion of the popularity of political positions remains an open empirical question
that also has to consider other social media platforms, as for example YouTube or
Instagram, that have been disregarded so far.
Altogether, empirical research involving popularity cues, especially relating to
political media content, is still rare. While data on the effects of formal factors
like links and pictures are collected by social media companies, little is known
about the role of content elements of messages and media items. Further, political
communication research that sheds light on the behavioral, cognitive, and attitu-
dinal consequences of popularity cues is in its infancy. In this early stage, consist-
ent conclusions cannot be derived. Since the effects of popularity cues are likely
to underlie specic boundary conditions, further research is needed to clarify how
the personal characteristics and features of political messages modify the effects
of popularity cues on the behaviors, cognitions, and attitudes of the audience.
Media effects and information processing theories suggest investigating concepts
such as controversy and unexpectedness on the content level, as well as involve-
ment, need for orientation, and opinion certainty on the level of personal charac-
teristics. Applying these basic concepts to analyze the effects of popularity cues in
the context of political communication is likely to enhance our understanding of
how Likes and Shares shape political behavior, cognitions, and attitudes and why
they sometimes fail to show the expected effects. Taken together, popularity cues
extend the features of political messages commonly considered in research on of-
ine communication and, as the debate around social bots shows, become part of
a political issue itself. Highlighting the premises and outcomes of popularity cues
in the realm of political communication research is thus a desirable approach for
the future.
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References
An, J., Quercia, D., & Crowcroft, J. (2013). Fragmented social media: A look into selective
exposure to political news. Proceedings of the 22nd International Conference on
World Wide Web, 51–52. doi:10.1145/2487788.2487807
Aragones, E., & Neeman, Z. (2000). Strategic ambiguity in electoral competition. Journal
of Theoretical Politics, 12(2), 183–204. doi:10.1177/0951692800012002003
Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marke-
ting Research, 49(2), 192–205. doi:10.1509/jmr.10.0353
Bader, C., Fuchs, K., Güthlein, C., Kamm, O., Schunk, T., & Maurer, M. (2015). Die Wahl
in 140 Zeichen – Twitter als Kommunikationsplattform für Politik, Medien und Bürger
im Bundestagswahlkampf 2013 [The election in 140 characters]. Politische Psycholo-
gie, 4(1), 5–22.
Bobkowski, P. S. (2015). Sharing the news effects of informational utility and opinion lead-
ership on online news sharing. Journalism & Mass Communication Quarterly, 92(2),
320–345. doi:10.1177/1077699015573194
Boehmer, J., & Tandoc, E. C. (2015). Why we retweet: Factors inuencing intentions to
share sport news on Twitter. International Journal of Sport Communication, 8(2), 212–
232. doi:10.1123/ijsc.2015-0011
Brandtzaeg, P. B., & Haugstveit, I. M. (2014). Facebook likes: a study of liking practices
for humanitarian causes. International Journal of Web Based Communities, 10(3),
258–279. doi:10.1504/IJWBC.2014.062942
Brewer, M. B. (1991). The social self: On being the same and different at the same
time. Personality and Social Psychology Bulletin, 17(5), 475–482. doi:10.1177/
0146167291175001
Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and
Social Psychology, 42(1), 116–131.
Castillo, C., El-Haddad, M., Pfeffer, J., & Stempeck, M. (2014). Characterizing the life
cycle of online news stories using social media reactions. Proceedings of the 17th ACM
Conference on Computer Supported Cooperative Work & Social Computing, 211–
223. doi:10.1145/2531602.2531623
Choi, J. (2016). Why do people use news differently on SNSs? An investigation of the role
of motivations, media repertoires, and technology cluster on citizens’ news-related ac-
tivities. Computers in Human Behavior, 54, 249–256. doi:10.1016/j.chb.2015.08.006
Corcoran, K., Crusius, J., & Mussweiler, T. (2011). Social comparison: Motives, standards,
and mechanisms. In D. Chadee (Ed.), Theories in social psychology (pp. 119–139).
Oxford: Wiley-Blackwell.
de Vries, L., Gensler, S., & Leeang, P. S. H. (2012). Popularity of brand posts on brand
fan pages: An investigation of the effects of social media marketing. Journal of Interac-
tive Marketing, 26(2), 83–91. doi:10.1016/j.intmar.2012.01.003
Eilders, C. (2006). News factors and news decisions. Theoretical and methodological ad-
vances in Germany. Communications, 31(1), 5–24. doi:10.1515/COMMUN.2006.002
Facebook (2016). Help center. Retrieved from https://www.facebook.com/help/
110920455663362
Fields, J. M., & Schuman, H. (1976). Public beliefs about the beliefs of the public. Public
Opinion Quarterly, 40(4), 427–448. doi:10.1086/268330
https://doi.org/10.5771/2192-4007-2018-2-80, am 28.06.2018, 16:53:11
Open Access - - https://www.nomos-elibrary.de/agb
227
Porten-Cheé/Haßler/Jost/Eilders/Maurer | Popularity cues in online media (Perspectives)
Gabielkov, M., Ramachandran, A., Chaintreau, A., & Legout, A. (2016). Social clicks:
What and who gets read on Twitter? Paper presented at the ACM SIGMETRICS / IFIP
Performance 2016. Retrieved from https://hal.inria.fr/hal-01281190/document
Gaffney, D., & Puschmann, C. (2014). Data collection on Twitter. In K. Weller, A. Bruns, J.
Burgess, M. Mahrt, & C. Puschmann (Eds.), Twitter and society (pp. 55–67). New
York, NY: Lang.
Gao, L. (2016). Motives for posting and liking on social media: Comparing differences
between Chinese and European users (Master’s Thesis). Retrieved from http://essay.
utwente.nl/69110/
Gerlitz, C., & Helmond, A. (2013). The like economy: Social buttons and the data-inten-
sive web. New Media & Society, 15(8), 1348–1365. doi:10.1177/1461444812472322
Graber, D. (1990). Seeing is remembering. How visuals contribute to learning from televi-
sion news. Journal of Communication, 40(3), 134–156. doi:10.1111/j.1460-2466.1990.
tb02275.x
Habermas, J. (2006). Political communication in media society: Does democracy still enjoy
an epistemic dimension? The impact of normative theory on empirical research. Com-
munication Theory, 16(4), 411–426. doi:10.1111/j.1468-2885.2006.00280.x
Hartmann, T. (Ed.). (2009). Media choice: A theoretical and empirical overview. New
York, NY: Routledge.
Hartmann, T., & Dohle, M. (2005). Publikumsvorstellungen im Rezeptionsprozess. Pub-
lizistik, 50(3), 287–303. doi:10.1007/s11616-005-0133-5
Hayes, R. A., Carr, C. T., & Wohn, D. Y. (2016). One click, many meanings: Interpreting
paralinguistic digital affordances in social media. Journal of Broadcasting & Electronic
Media, 60(1), 171–187. doi:10.1080/08838151.2015.1127248
Haßler, J., Jost, P. B. & Maurer, M. (2016, November, 09–12). Sharing the news – Face-
book shares as relevance indicators. Paper presented at ECREAs 6th European Com-
munication Conference, Prague.
Haßler, J., Maurer, M., & Holbach, T. (2014). Vorsprung durch Technik? Die Analyse jour-
nalistischer Online-Angebote mit Hilfe automatisierter Verfahren [Advancement
through technology? The analysis of journalistic online-content by using automated
tools]. Studies in Communication and Media, 3(2), 180–204.
Jin, S. V., Phua, J., & Lee, K. M. (2015). Telling stories about breastfeeding through Face-
book: The impact of user-generated content (UGC) on pro-breastfeeding attitudes.
Computers in Human Behavior, 46, 6–17. doi:10.1016/j.chb.2014.12.046
Jost, P. B. & Maurer, M. (2016, January, 28–30). Online-Popularitätsindikatoren als Indi-
katoren für Persuasionserfolg? Zum Innovationspotenzial sozialer Medien für die Me-
dienwirkungsforschung [Online popularity cues as indicators for persuasive success?
The innovative potential of social media for media effects research]. Paper presented at
Jahrestagung der Fachgruppe Rezeptions- und Wirkungsforschung in der DGPuK,
Amsterdam.
Jungherr, A. (2014). The logic of political coverage on Twitter: Temporal dynamics and
content. Journal of Communication, 64(2), 239–259. doi:10.1111/jcom.12087
Keyling, T., & Jünger, J. (2016). Observing online content. In G. Vowe & P. Henn (Eds.),
Political communication in the online world. Theoretical approaches and research de-
signs (pp. 183–200). New York, NY: Routledge.
https://doi.org/10.5771/2192-4007-2018-2-80, am 28.06.2018, 16:53:11
Open Access - - https://www.nomos-elibrary.de/agb
228 Studies in Communication and Media, 7. Jg., 2/2018
Full Paper
Keyling, T., Kümpel, A., & Brosius, H.-B. (2015). Die Darstellung von Politikern auf
YouTube: Die Rolle von Humor in der Politikvermittlung [The depiction of politicians
on YouTube: The role of humor in political communication]. In K. Imhof, R. Blum, H.
Bonfadelli, O. Jarren, & V. Wyss (Eds.), Demokratisierung durch Social Media?
(pp.113–132). Wiesbaden: Springer VS.
Knobloch-Westerwick, S., Sharma, N., Hansen, D. L., & Alter, S. (2005). Impact of popu-
larity indications on readers’ selective exposure to online news. Journal of Broadcast-
ing and Electronic Media, 49(3), 296–313. doi:10.1207/s15506878jobem4903_3
Kümpel, A. S., Karnowski, V., & Keyling, T. (2015). News sharing in social media: A re-
view of current research on news sharing users, content, and networks. Social Media +
Society, 1(2), 1–14. doi:10.1177/2056305115610141
Lau, R. R., Sigelman, L., & Rovner, I. B. (2007). The effects of negative political Campaigns:
A meta-analytic reassessment. Journal of Politics, 69(4), 1176–1209. doi:10.1111/
j.1468-2508.2007.00618.x
Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratications and
prior experience. Computers in Human Behavior, 28(2), 331–339. doi:10.1016/j.
chb.2011.10.002
Lee, E.-J., & Jang, Y. J. (2010). What do others’ reactions to news on Internet portal sites
tell us? Effects of presentation format and readers’ need for cognition on reality per-
ception. Communication Research, 37(6), 825–846. doi:10.1177/0093650210376189
Lee, E.-J., & Nass, C. (2002). Experimental tests of normative group inuence and repre-
sentation effects in computer-mediated communication. Human Communication Re-
search, 28(3), 349–381. doi:10.1111/j.1468-2958.2002.tb00812.x
Matthes, J. (2006). The need for orientation towards news media: Revising and validating
a classic concept. International Journal of Public Opinion Research, 18(4), 422–444.
doi: 10.1093/ijpor/edh118
Matthes, J., Morrison, K. R., & Schemer, C. (2010). A spiral of silence for some: Attitude
certainty and the expression of political minority opinions. Communication Research,
37(6), 774–800. doi:0.1177/0093650210362685
Maurer, M., & Reinemann, C. (2016). Do uninvolved voters rely on visual message ele-
ments? A test of a central assumption of the ELM in the context of televised debates.
Politische Psychologie/Journal of Political Psychology, 4, 235–251.
Meier, F., Elsweiler, D. C., & Wilson, M. L. (2014). More than liking and bookmarking?
Towards understanding Twitter favouriting behaviour. Eighth International AAAI
Conference on Weblogs and Social Media.
Messing, S., & Westwood, S. J. (2014). Selective exposure in the age of Social Media: En-
dorsements trump partisan source afliation when selecting news online. Communica-
tion Research, 41(8), 1042–1063. doi:10.1177/0093650212466406
Mitchell, A., & Page, D. (2013). The role of news on Facebook. Common yet incidental.
Pew Research Center. Retrieved from http://www.journalism.org/les/2013/10/
facebook_news_10-24-2013.pdf
Mitchell, A., & Page, D. (2014). State of the news media. Pew Research Center. Retrieved
from http://www.journalism.org/les/2014/03/Overview.pdf
Noelle-Neumann, E. (1993). The spiral of silence: Public opinion – our social skin. Chica-
go, IL: Chicago University Press.
https://doi.org/10.5771/2192-4007-2018-2-80, am 28.06.2018, 16:53:11
Open Access - - https://www.nomos-elibrary.de/agb
229
Porten-Cheé/Haßler/Jost/Eilders/Maurer | Popularity cues in online media (Perspectives)
Oh, S.-K. (2014). What’s in a “like”? Inuence of news audience engagement on the delib-
eration of public opinion in the digital public sphere (Doctoral dissertation). Retrieved
from http://drum.lib.umd.edu/handle/1903/15949
Oh, S.-K., & Syn, S. Y. (2015). Motivations for sharing information and social support in
social media: A comparative analysis of Facebook, Twitter, Delicious, YouTube, and
Flickr. Journal of the Association for Information Science and Technology, 66(10),
2045–2060. doi:10.1002/asi.23320
Peter, C., Rossmann, C., & Keyling, T. (2014). Exemplication 2.0. Roles of direct and in-
direct social information in conveying health messages through social network sites.
Journal of Media Psychology, 26(1), 19–28. doi:10.1027/1864-1105/a000103
Perrin, A. (2015). Social networking usage: 2005–2015. Pew Research Center. Retrieved
from http://www.pewinternet.org/2015/10/08/2015/Social-Networking-Usage-2005-
2015/
Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion. Central and
peripheral routes to attitude change. New York, NY: Springer.
Presser, S. (1990). Can changes in context reduce vote overreporting in surveys? Public
Opinion Quarterly, 54(4), 586–593. doi:10.1086/269229
Reinard, J. C. (1988). The empirical study of the persuasive effects of evidence: The status
after fty years of research. Human Communication Research, 15(1), 3–59.
doi:10.1111/j.1468-2958.1988.tb00170.x
Reinecke, L., & Trepte, S. (2014). Authenticity and well-being on social network sites: A
two-wave longitudinal study on the effects of online authenticity and the positivity bias
in SNS communication. Computers in Human Behavior, 30, 95–102. doi:10.1016/j.
chb.2013.07.030
Rogers, S. (2014, March 10). What fuels a Tweet’s engagement? Retrieved from https://
blog.twitter.com/2014/what-fuels-a-tweets-engagement
Scharkow, M., & Vogelgesang, J. (2011). Measuring the public agenda using search engine
queries. International Journal of Public Opinion Research, 28(1), 109–119.
doi:10.1093/ijpor/edq048
Singer, J. B. (2014). User-generated visibility: Secondary gatekeeping in a shared media
space. New Media & Society, 16(1), 55–73. doi:0.1177/1461444813477833
Smith, S. M., Fabrigar, L. R., MacDougall, B. L., & Wiesenthal, N. L. (2008). The role of
amount, cognitive elaboration, and structural consistency of attitude-relevant knowl-
edge in the formation of attitude certainty. European Journal of Social Psychology,
38(2), 280–295. doi:10.1002/ejsp.447
Snyder, C. R., & Fromkin, H. S. (1980). Uniqueness: The human pursuit of difference.
New York, NY: Plenum Press.
Sundar, S. S., & Nass, C. (2001). Conceptualizing sources in online news. Journal of Com-
munication, 51(1), 52–72. doi:10.1111/j.1460-2466.2001.tb02872.x
Trilling, D., Tolochko, P., & Burscher, B. (2017). From newsworthiness to shareworthiness:
How to predict news sharing based on article characteristics. Journalism & Mass Com-
munication Quarterly, 94(1), 38–60. doi:10.1177/1077699016654682
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases.
Science, 185(4157), 1124–1131. doi:10.1126/science.185.4157.1124
Twitter (2016). Liking a Tweet. Retrieved from https://support.twitter.com/articles/
20169874
https://doi.org/10.5771/2192-4007-2018-2-80, am 28.06.2018, 16:53:11
Open Access - - https://www.nomos-elibrary.de/agb
230 Studies in Communication and Media, 7. Jg., 2/2018
Full Paper
Weber, P., & Wirth, W. (2013). Nachrichtenfaktoren und Relevanzattribution. Der Einuss
von Nachrichtenfaktoren auf Relevanzurteile von Rezipienten und die moderierende
Rolle von Civic Pride [News values and relevance attribution. The impact of news
factors on recipients’ judgments of relevance and the moderating role of civic pride].
Medien & Kommunikationswissenschaft, 62(4), 514–531. doi:10.5771/1615-634x-
2013-4-514
Webster, J. G. (2011). The duality of media: A structurational theory of public attention.
Communication Theory, 21(1), 43–66. doi:10.1111/j.1468-2885.2010.01375.x
Woolley, S. C. (2016) Automating power: Social bot interference in global politics. First
Monday, 21(4). Retrieved from https://rstmonday.org/ojs/index.php/fm/article/view/
6161/5300
Zerback, T., Koch, T., & Krämer, B. (2015). Thinking of others. Effects of implicit and ex-
plicit media cues on climate of opinion perceptions. Journalism & Mass Communica-
tion Quarterly, 92(2), 421–443. doi:10.1177/1077699015574481
