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Participatory Propaganda: The Engagement of Audiences in the Spread of Persuasive Communications


Abstract and Figures

Existing research on aspects of propaganda in a digital age tend to focus on isolated techniques or phenomena, such as fake news, trolls, memes, or botnets. Providing invaluable insight on the evolving human-technology interaction in creating new formats of persuasive messaging, these studies lend to an enriched understanding of modern propaganda methods. At the same time, the true effects and magnitude of successful influencing of large audiences in the digital age can only be understood if target audiences are perceived not only as 'objects' of influence, but as 'subjects' of persuasive communications as well. Drawing from vast available research, as well as original social network and content analyses conducted during the 2016 U.S. presidential elections, this paper presents a new, qualitatively enhanced, model of modern propaganda-"participatory propaganda"-and discusses its effects on modern democratic societies.
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Participatory Propaganda:
The Engagement of Audiences in the Spread of Persuasive Communications
Alicia Wanless
Director of Strategic Communications,
SecDev Foundation
Michael Berk
Visiting Research Fellow,
Centre for Cyber Security and International
Relations Studies, University of Florence
Related network visualisations referenced in this paper could not be included
due to file size restrictions on uploading. Happy to provide if desired.
Existing research on aspects of propaganda in a digital age tend to focus on isolated techniques
or phenomena, such as fake news, trolls, memes, or botnets. Providing invaluable insight on the
evolving human-technology interaction in creating new formats of persuasive messaging, these
studies lend to an enriched understanding of modern propaganda methods. At the same time, the
true effects and magnitude of successful influencing of large audiences in the digital age can
only be understood if target audiences are perceived not only as ‘objects’ of influence, but as
‘subjects’ of persuasive communications as well. Drawing from vast available research, as well
as original social network and content analyses conducted during the 2016 U.S. presidential
elections, this paper presents a new, qualitatively enhanced, model of modern propaganda –
“participatory propaganda” - and discusses its effects on modern democratic societies.
Keywords: propaganda, Facebook, social network analysis, content analysis, politics
Participatory Propaganda:
The Engagement of Audiences in the Spread of Persuasive Communications
Rapidly evolving information communications technologies (ICTs) have drastically
altered the ways individuals engage in the public information domain, including news ways of
becoming subjected to external influencing. By merging together tech-enabled formats of
persuasive content, automated dissemination capabilities and targeted audience engagement in
content propagation, a savvy propagandist can acquire enhanced means of swaying opinions
around the world. By obfuscating the origins of such propagandistic content through audience
participation via the internet and social networks the propagandist can also increase its
receptivity and influence effects. Tactics encouraging and enabling target audiences to not just
spread, but also create and adapt propaganda messages, appear to be more effective means of
mass persuasion given that people tend to find recommendations from their personal social
network more credible than others (Nielson, 2015). Such subtle mass persuasion, through and by
means of personal networks, is problematic in liberal democracies founded on the premise that
freedom of choice by citizens on political matters is expected to inform public decision-making
and power structures (Lippman, 1922; Irwin, 1919, Marlin 2011).
This paper is broken out into three sections. In the first, an extensive multidisciplinary
literature review aggregates individual studies published recently that analyze the known digital,
behavioural and psychological tactics available to propagandists aiming to engage target
audiences online. Extensive research conducted by various scholars over recent years on new
ICT tools, social networks, influence tactics and their manifested effects on consumers of online
information, and in particular on their political choices, has been instrumental in acquiring the
first appreciation for the scale, complexity and social repercussions of modern persuasive
communications. In the second section, the paper draws on original research conducted during
the 2016 U.S. presidential elections to analyze how Trump supporters applied these tactics to
engage Facebook followers in the promotion of persuasive content, thus encouraging them to
become propagandists themselves. In the conclusion, the research results are placed into the
broad context of the emerging information environment providing some observations on possible
repercussions for citizens’ political engagement and arguing that further work and modelling of
digital propaganda is required to better understand the risks to liberal democracy associated with
using such techniques.
Literature Review
Modern Propaganda and the Evolution of its Participatory Model
Propaganda is a much-contested term. This difficulty in defining propaganda, stems in
part from its complicated relationship with liberal democracies, given that public opinion is
expected to influence political decision-making and the act of manipulating it calls into question
the agency of voters, or even the democratic system itself. As John S. Dryzek explains there is a
long history in political theory "from Plato to Habermas which equates rhetoric with emotive
manipulation of the way points are made, propaganda and demagoguery at an extreme, thus
meriting only banishment from the realm of rational communication." (2000, 52) Such concerns
were not assuaged by early pioneers in the field of public relations either, who fearing how easily
public opinion could be swayed saw domestic propaganda as an acceptable tool for the
management of popular views. (Dewey, 1925; Bernays, 1928; Lasswell, 1934; Lippmann, 1922).
At the same time, propaganda began to acquire a pejorative connotation as it was “associated
mainly with totalitarian regimes and war efforts” and “was perceived as a threat to liberal
democracies.” (Ross, 2002, 17). In turn, similar activities aimed at influencing domestic public
opinion became known by other terms such as public affairs or public relations (Moloney, 2006),
and those aimed at persuading external audiences as public diplomacy or information operations
(Garrison, 1999).
Traditionally, propaganda has been described as the use of persuasive information to
manipulate a target audience into a behaviour desired by the propagandist. (Bernays, 1928;
Lasswell, 1948; Ellul, 1965; Marlin, 2013; Jowett & O’Donnell, 2015). In this top-down
communications model, the sender-receiver roles were typically static with the propagandist
(government, corporate, military, political) issuing persuasive messaging aimed at achieving a
specific outcome among the target audience (general public). This classic understanding of
propaganda, however, must be adapted in a Digital Age. With the internet and social media, the
traditional separation between ‘the propagandist’ and ‘target audience’ is rapidly blurring with
the latter beginning to play a more significant role in spreading propagandistic content and
influencing others through personal networks – and this is much more dangerous, as people are
more likely to believe those familiar to them (Garrett & Weeks, 2013) or those they view as
influential (Turcotte et al, 2015).
While neither deliberately manipulative messaging, nor proselytization are new
techniques in the time-honoured tradition of winning hearts and minds, the speed and scale at
which audiences can be swayed and co-opted into spreading persuasive content have
significantly increased thanks to the internet. Likewise, as people are increasingly plugged in and
dependent on ICTs, the reach of propaganda – particularly if it resonates with a target audience –
can become all-encompassing and difficult to escape.
In this context, to understand the emerging phenomena in persuasive communications, a
new concept is suggested – participatory propaganda – building on Jowett & O’Donnell’s
1 definition of propaganda: Participatory propaganda is the deliberate, and systematic attempt to
shape perceptions, manipulate cognitions and direct behaviour of a target audience while seeking
to co-opt its members to actively engage in the spread of persuasive communications, to achieve
a response that furthers the desired intent of the propagandist.
Participatory propaganda moves beyond a traditional, unidirectional “one-to-many” form
of communication, to a “one-to-many-to-many more” form where each ‘target’ of influence (an
individual or group which is the object of persuasion) can in theory become the new ‘originator’
(subject) of content production and distribution, spreading persuasive messaging to others in a
‘snowball’ effect. The original propaganda message triggers, reinforces, or exacerbates pre-
existing sentiments associated with the message in a way that prompts the consumer to actively
engage in its propagation through available social networks, both on and off-line. Even if
modified through the consumer’s own interpretation, the core message remains intact, and
sometimes could even acquire a ‘new life’ (e.g. a new wave of content dissemination). At the
same time, online monitoring tools enable the original propagandist to follow and assess the
spread of their messaging, adapting strategies in a constant feedback loop and inserting
additional content, as and if required.
Participatory propaganda offers the ability to truly dominate the information space
through volume of messaging, delivered through a mix of real people and automated accounts,
effectively making it difficult to discern where fake ends and authenticity begins.
1 The original definition of propaganda by Jowett & O’Donnell reads “Propaganda is the deliberate and
systematic attempt to shape perceptions, manipulate cognitions, and direct behavior to achieve a response that
furthers the desired intent of the propagandist.See, Jowett & O’Donnell, 2015 page 7
Studying modern political campaigns with their increasing reliance on social networks
demonstrates the case in point. While a modern political campaign continues to fit the traditional
model of propaganda, as defined by Jowett and O’Donnell, namely the “deliberate, systematic
attempt to shape perceptions” (e.g. popular opinions of Trump supporters) such that it “directs
behaviour to achieve a response” (e.g. support for Trump in the form of online participation and
voting) furthering “the desired intent of the propagandist” (e.g. the Trump campaign), it
increasingly acquires the characteristics of a participatory propaganda model. Based on
numerous and recently published academic studies, as well as our own analysis of the U.S.
presidential campaign by Donald J. Trump, six digital tactics for engaging a target audience
online to draw them into active dissemination of persuasive messaging were identified. The order
selected for the presentation of these tactics is important as it corresponds to the order of steps a
propagandist would take to develop and disseminate the original persuasive messaging:
1. Hyper-Targeted Audience Analysis
In the emerging field of behavioural advertising, marketers collect information about
what people do online to position extremely targeted ads in front of users (Matthew, 2017).
Trackers that facilitate the collection of this information were found in 114 websites supporting
Trump (Albright, 2016a). This tracking information can be used to segment target audiences
based on psychographics (Psychometric Centre, 2017), which can be extremely accurate at
assessing how a user thinks and what might provoke them into action (Cohen, 2017). Social
networks allow you to apply this knowledge to targeted ad placement (Solon, 2017), which the
Trump campaign did (Nix, 2016). Such highly targeted audience analysis also facilitates the
creation of provocative content and the identification of online echo chambers.
2. Provocative Content
At least three types of content aimed at provoking a response among target audiences
were used by Trump supporters: fake news, memes, and data leaks.
Fake News. Facebook defined fake news as “articles that purport to be factual, but which
contain intentional misstatements of fact with the intention to arouse passions, attract viewership,
or deceive.” (Weedon et al, 2017). Since lies spread faster online than the truth (Silverman,
2015), fake news has become a global problem (Connolly et al, 2016). Conspiracy theories, often
a feature of fake news, reduce complex issues to “binary opposition, simplifying - and
misrepresenting - the political space,” (Moore, 2015, 9) and a person’s degree of partisanship is
linked to their likelihood of believing conspiracy theories or fake news (Frankovic, 2016).
Governments and non-state actors alike are spreading disinformation online (Weedon et al,
2017), including Trump, who spread fake news during the campaign (Maheshwari, 2017). When
such content was shared by known and trusted opinion leaders on Facebook, they tended to
influence audience perspectives (Turcotte et al, 2015), and indeed, stories favouring Trump were
shared nearly four times more than those supporting Clinton (Allcott & Gentzkow, 2017).
Memes. Memes are often humorous phrases, images or videos that are copied or adapted
with slight variations and then shared online (Blackmore, 2000). During the 2016 election,
Facebook groups sprang up dedicated to sharing “dank memes” (Hsu, 2016) and a controversial
Silicon Valley tech entrepreneur funded a “meme factory” to support Trump (Hern, 2016). So-
called “meme battalions” created visual content that “relentlessly drew attention to the tawdriest
and most sensational accusations against Clinton, forcing mainstream media outlets to address
topics – like conspiracy theories about Clinton’s health – that they would otherwise ignore.”
(Schreckender, 2017)
Memes reduce the public policy debate to shallow sound bites and ridicule stripped of
contextualized understanding of available political choices (McClure, 2016). This contributes to
‘media endarkenment’ reducing complex political issues to simplified entertainment and
misinformation (Lazitski, 2014).
Leaks have long played a role in American political propaganda (Castronovo, 2014).
According to the Oxford Dictionary, a leak is the “intentional disclosure of secret information”
(2017). During the 2016 election, Clinton was dogged by several leaks, which could have been
one factor affecting her standing in public opinion polls (Enten, 2016). These included the
hacking of her Chief of Staff John Podesta’s emails (Frank, 2016), the leaking of comments she
made about Bernie Sanders supporters (Democracy Now, 2016) and the continued FBI
investigations around the private email server Clinton used while serving as Secretary of State
(exposed through a hack) hampered her campaign (Williams, 2016).
Provocative content aims to elicit an emotional response among a target audience,
provoking them into participating in a propaganda campaign. This can be an effective method of
target audience engagement, particularly if the content is fed through existing channels where an
audience already receives information, such as an online echo chamber.
3. Echo Chambers
Drawing from the insights gained in hyper-targeted content analysis, a propagandist can
identify online echo chambers with specific audiences who can now be targeted with provocative
content to which they are most likely to react. An online echo chamber is a digital space where
content reflecting a specific point of view reverberates, exposing those within it to only that one
prevailing perspective. Digital technologies enable the quick creation of echo chambers or filter
bubbles (Breitenbach, 2017), in part through algorithms that sort information, (Bakshy et al,
2015) but more so by the choices individuals make about content consumption (Bessi et al, 2016;
Grömping, 2014). Once inside an echo chamber, a user is fed content fitting pre-existing views
and preferences, such as political party affiliation (Wall Street Journal, 2016).
Echo chambers identified during the 2016 election were strengthened by a growing
animosity between political camps, (Thompson, 2016) as well as a lack of media trusted by both
Republicans and Democrats (Pew, 2016a), and thus information exchange was hindered across
party lines (Mitchell et al 2016). Moreover “political echo chambers not only isolate one from
opposing views, but also help to create incubation chambers for blatantly false (but highly salient
and politicized) fake news stories.” (Pennycook et al 2017)
Echo chambers supporting Trump shared fakes news during the election (Dreyfus, 2017;
BBC, 2016), with some hyper-partisan right-wing Facebook communities feeding followers 38%
fake content (Silverman et al, 2016).
4. Manipulating Feed & Search Algorithms
Provocative content is then given a boost by manipulating important online algorithms.
Internet giants, such as Facebook (Facebook, 2017) and Google (Google, 2017), use algorithms
to provide users with content they think is wanted (Facebook 2017). Search returns have been
found to sway voter decisions (Epstein & Robertson, 2015) and algorithms enable echo chamber
development (Algorithm Auditing Research Group, 2016; Barret, 2016).
Algorithms also had a role in the 2016 elections. Fake news supporting Trump trended on
Facebook through algorithms (Lee, 2016). Google search autocompletes and returns favoured
Trump, spreading false information with a far-right bias (Solon & Levin, 2016).
Google Search algorithms can be gamed in at least two ways:
Hyperlinking & Seeding of Content: Posting content, such as fake news, on multiple
websites and linking back and forth between sources helps boost content in Google search
returns (Moz, 2107), and if nothing else, can bury opposing information from appearing in the
first pages of returns. Indeed, in one study using hyperlink network analysis pro-Trump websites
were found to be choking out mainstream media (Albright, 2016b).
Botnets & Automated Posting: Lobby groups (Monbiot, 2011), governments (The
Intercept, 2015), and businesses (Kabin, 2013), are among the many who are using astroturfing
and bots to distort the information space for strategic purposes. Posting fake comments and
reviews aims to harness the cognitive bias of “social proof” (Ambled & Bui, 2014). Botnets (and
heavily automated posting) can manipulate algorithms. Twitter bots gamed Google’s algorithm
for displaying “real time news” into promoting disinformation during a 2010 senate election in
Massachusetts (Mustafaraj & Metaxas, 2010).
During the 2016 election, pro-Trump Twitter Bots dominated discussion about the U.S.
election 5 to 1 over pro-Clinton messaging, and “strategically colonized pro-Clinton hashtags,”
according to Oxford Internet Institute research (Kollanyi & Howard, 2016). Bots also accounted
for nearly one-fifth of online discussion about the election (Bessi & Ferrara, 2016), negatively
affecting political discourse by drowning opposing views. This domination in online discourse
helps explain Trump’s success in Google search rankings.
5. Encouraging Followers to Action
Once inside echo chambers followers can be encouraged, through posts and email
distribution lists (Albright, 2016a; Plouffe, 2010), to participate in the spread of propaganda,
including: sharing messages; co-opting or borrowing influencer accounts to share content
(Katalenas, 2016); or encouraging trolling (Cheng et al, 2017; Buckels et al, 2014) to stifle
To many, Trump is a troll (Silver, 2015; Offman, 2016; Lapowsky & Marshall, 2017) but
he was also supported by a legion of online trolls during the election (Marantz, 2016), spreading
disinformation (Kang, 2016; Gallucci, 2016) and attacking Clinton supporters online
(Chmielewski, 2016). Some online communities, such as the United States Freedom Army (who
believes the left is engaging the right in a civil war) offered its members a monthly directive on
actions to take on Twitter, and elsewhere in the spread of their content and support for Trump
(Lotan, 2016).
6. Using Traditional Media
Media play a critical role in furthering political agendas (Wodak, 2013; Engel & Wodak,
2009; Engel & Wodak, 2012); after all, “the media are a key element in the construction of
public understanding.” (Philo, 2008, 539) Rates of politician media coverage correlate to popular
support levels (Vliegenthart et al, 2012) and Trump was consistently mentioned more on
television, online, and social media (Wanless, 2016). By the start of the primary election
campaign in early 2016, Trump had been enjoying “more nightly news coverage than the entire
Democratic field combined.” (Borchers, 2015) Media coverage can be earned in at least three
Trending Online. Simply trending online can lead to media coverage. Indeed, a Google
news search for the exact terms “Trending on Twitter” on 27 April 2017 returned 371,000 results
– with 14,000 published within that past week. (Of course, as noted above, bots and automated
posting can be used to distort what trends).
Stage a Scandal. Media savvy populist politicians are particularly adept at this. Through
a “right-wing populist perpetuum mobile” (Wodak, 2013), populists stage scandals to gain media
attention, provoking opposition to attack, then distorting ensuing debate to position themselves
as victims not tolerated by a biased system. Such scandals can usually be interpreted in multiple
ways. Trump used this technique when retweeting a campaign supporter’s image post. In the
picture, adapted from Clinton’s campaign material, the Trump supporter had added a symbol
similar to the Star of David. Opponents decried the use of the symbol as anti-Semitic (Jacobson,
2016). The Trump campaign claimed the liberal media had misinterpreted a Sherriff’s star and
was biased against him (Trump, 2016).
Commune with the news. Media, politicians and online communities have a deeply
interconnected relationship. The Colombia Journalism Review identified a “right wing media
network anchored around Breitbart” in analysing more than 1.25 million stories posted online
from 1 April 2015 to 8 November 2016. This “distinct and insulated media system” used social
media to spread a “hyper-partisan perspective”, but also “strongly influenced the broader media
agenda, in particular coverage of Hillary Clinton.” (Benkler et al, 2016).
As these studies demonstrate, many of these techniques when combined together could
be used to encourage followers and co-opt audiences into active participation, becoming
propagandists for a cause and thus deliberately working to persuade their own personal networks
too. To evaluate the extent of their application during the U.S. presidential elections an original
study of Facebook pro-Trump pages was conducted to assess how audiences might have been
engaged in the creation and distribution of persuasive political messaging.
Modelling Participatory Propaganda
Methodology & Data
The study includes social network and content analyses undertaken on 17 Facebook
pages, using data related to a month-long period leading up to the 2017 election (7 October to 7
November 2016). These pages included three that supported Trump during the election, as well
as seven conservative-leaning and seven liberal-leaning media outlets. The digital tactics
outlined in the previous section were used as a frame for investigation.
Social network analysis has shown to be an effective method to study online group
dynamics, information diffusion processes, and political polarisation in social media (Gruzd &
Roy, 2014; Gruzd & Tsyganova, 2015). Facebook pages and groups have been analysed to
identify echo chambers (Grömping, 2014; Bakshy et al, 2014; Del Vicario et al, 2016). And
content analysis has been used to assess right-wing populist rhetoric in media (Bos et al, 2010,
2011, Sheets et al, 2015).
Facebook was selected for this research as 79% of American adults who use the internet
also use this social network (Pew, 2016b), making it the most popular and thus representative
social media for studying politics in the U.S.
The data collection process was executed using the publicly available Facebook Graph
API with the help of online application - Netvizz (Rieder, 2013). Only publicly available data
was used. The data, in the form of communication networks among Facebook users, was
analysed using Social Network Analysis (SNA) (Scott, 1988, 2011). Network visualisations were
created using the open-source social network analysis software, Gephi (Bastion et al, 2009).
The pages analysed are as follows:
Table 1
Facebook Pages Analysed
Trump Supporters
Right-Leaning Media
Left-Leaning Media
Citizens for Trump
CBS News
Eagle Rising
The Glenn Beck Program
Wake Up & Reclaim America
Fox News
The Sean Hannity Show
The New York Times
The Drudge Report
The Blaze
The Washington Post
The three pro-Trump pages were chosen as a sampling of those supporting his candidacy,
with one showing its open support through the name (Citizens for Trump), another having been
found spreading fake news (Silverman et al, 2016) supporting Trump (Eagle Rising), and a third
standing out as a node in initial, exploratory network analysis (Wake Up & Reclaim America).
Drawing from a Pew Research Centre survey on Political Polarization and Media Habits
(Mitchell et al, 2016), seven media outlets trusted consistently by respondents who self-identified
as liberal or conservative were selected. One substitute was made on the Conservative-leaning
side, which was Infowars, given the role it played in the election (Finnegan, 2016). Media pages
were used to assess how pro-Trump pages were engaging with news outlets.
The following publicly available data for all of these pages was collected using Netvizz:
Facebook page like networks.
Beginning with an initial “seed” page, all of the other Facebook pages liked by the seed
are collected in a directed network of pages, meaning the data shows which page likes which.
Using an analytical took called Gephi, these networks can be visualised. The data in this pull also
included information regarding page categories, follower numbers, and rates of engagement.
Facebook page posts.
All of the posts made by these pages during the month leading up to the election (7
October to 7 November 2016) were also collected, including information regarding the type of
post, engagement rates and embedded links.
This Facebook page data was then analysed to answer the following questions:
Did pro-Trump Facebook pages share provocative content such as fake news,
memes, and data leaks?
Did pro-Trump Facebook pages constitute an echo chamber?
Was content shared on pro-Trump Facebook pages posted across multiple
websites? And how was this content reflected in Google Search returns?
Were followers of pro-Trump Facebook pages encouraged to action?
How did pro-Trump Facebook pages engage with media outlets?
Did pro-Trump Facebook pages share provocative content such as fake news, memes, and
data leaks?
The short answer is yes.
Fake News. The links shared to the three Trump supporting Facebook pages reviewed for
this study were mostly non-mainstream media. On average, link posts comprised 53.22% of
updates made by the pro-Trump pages. Eagle Rising shared more links than the other two
(83.25% of posts), with nearly half of those links (45.4%) pointing to the page’s own website, which contains coverage speculating on connections between Clinton, terrorists
and Nazis,2 for example, and the Clinton campaign’s alleged use of psychological warfare
(which in turn points back to another site shared by these pages called 3
After Breitbart, the most shared domain to Citizens for Trump was, a
blog that has posted many questionable articles on Hillary Clinton, including that she secretly
called for Trump’s assassination,4 had suffered a brain seizure,5 and that she had a gum and
immune disorder.6 During the period between 7 October to 7 November 2016, Citizens for Trump
shared 13 Gateway Pundit articles, accounting for 4.32% of all link posts, including one
speculating on Clinton’s health that enjoyed 319 shares on Facebook.7 Wake Up & Reclaim
America also shared 14 Gateway Pundit articles, including a post suggesting Clinton was
involved in having Supreme Court Justice Scalia assassinated.8
Memes. Following initial content analysis of photo posts to the pages analysed, and
drawing from a similar study of Breitbart posts (Renner, 2017), memes were counted by the total
number of photo posts made by the pro-Trump pages. Memes account for a considerable number
of posts on community Facebook pages such as Wake Up & Reclaim America. In analysis of
1330 posts made by Wake Up & Reclaim America in the month leading up to the 8 November
2016 election, nearly half were image posts. Nearly two-thirds of those photo posts were shared
by the page administrator from other Facebook user posts, pages or groups, such as Liberal
2 See:
3 See:
4 See:
5 See:
6 See:
7 See:
8 See:
Wackadoodles, indicating spread through a wider community. Memes were also shared by Eagle
Rising (14.79%) and Citizens for Trump (26.62%)
Table 2
Post Type by Pro-Trump Facebook Pages
Data Leaks. Hacks and leaks were certainly discussed online. All of the pro-Trump
pages assessed made mention of “Wikileaks”,9 a non-profit that aims to “open governments”,
which in that time frame had shared more of the leaked Podesta emails to its website. Of the
three Facebook pages analysed that supported Trump, 65 posts mentioned “Wikileaks” during
the month leading up to the 8 November election, accounting on average for 2.75% of all posts
made during that period. Both the conservative- and liberal- leaning media outlets analysed made
mention of “Wikileaks” in this timeframe too: the seven right-leaning pages mentioned
9 See:
“Wikileaks” 131 times accounting for 2.72% of all posts made on average, whereas the left-
leaning pages referenced it 47 times, or in just 0.46% of all posts.
Did pro-Trump Facebook pages constitute an echo chamber?
Yes, the three pro-Trump pages were part of a like-minded community, which shared
similar content.
A manual categorization of pages based on names and content reveals that the three pro-
Trump page like networks are decidedly part of right-leaning echo chambers. Nearly all (94.1%)
of the Citizens for Trump network are right-leaning, pro-Trump pages, while 82.7% of those
within the Eagle Rising network are. As the Wake Up & Reclaim America page contained over
5,000 pages, a sampling of 1,000 pages were manually categorized, representing 18.8% of the
total. While 67.8% of these were right-leaning pro-Trump pages, most other pages covered topics
reflected in Trump’s campaign rhetoric, such as pro-Christian, anti-Muslim, pro-military, pro-
police, anti-immigration, and pro-life views. If these topics are combined, the rate of pages
within the Wake Up & Reclaim America network that reflect views shared by Trump supporters
is 95.7%. Given that only two pages were found to express counter views – across all three page
networks – it is safe to say these networks comprise a filter bubble of sorts.
As noted earlier, the three pro-Trump Facebook pages shared more alternative media
sources than mainstream links in the month leading up to the 2016 election. Of those links shared
to the pro-Trump pages and pointing to the conservative- and liberal-leaning pages also analysed,
most were from either Fox or Breitbart. The page Eagle Rising shared none of the 14 media
pages analysed, and the 1143 links posted between 7 October and 7 November 2016 pointed to
just 14 websites, including
Was content shared on pro-Trump Facebook pages posted across multiple websites? And
how was this content reflected in Google Search returns?
Drawing from posts shared to the three pro-Trump pages in the lead up to the election, a simple
Google search of article titles sheds some light on how such networks function. In one example,
Eagle Rising shared an article from the blog the entitled “Hillary Clinton: Calls
Blacks Professional Never Do Wells”. This post garnered 157 shares on Facebook.
A Google search using the article’s title as exact terms, returns the original post, as well
as several nearly exact reprints on other sites, with some linking back to The Blacksphere article.
A search for The Blacksphere url returns 734 results, including posts from,, and Some of these links are posted by other users in
comment sections and online forums, and Sharescount10 suggests the URL was shared 12.5K
times across social networks. The article was also picked up by online trend aggregators like
Trendolizer,11 indicating the efforts to spread this content had some impact. Indeed, absent on the
first page of another search return (made in a separate web browser logged into a different
Google account) for the key words “Is Hillary Clinton a racist?” are any posts refuting the idea
she might be (See Annex A). 12
Were followers of pro-Trump Facebook pages encouraged to action?
The three pro-Trump pages all encouraged their audiences to participate. Citizens for
Trump and Eagle Rising, however, were arguably more successful than Wake Up & Reclaim
America, as demonstrated through the average rates of follower shares on Facebook posts.
All three pages encouraged followers to vote for Trump.
10 See:
11 See:
12 This experiment was then repeated in a different country, on another internet service provider, on a new
computer with similar results
Citizens for Trump and Eagle Rising, however, also asked followers to share and spread
messages, which might account for the higher percentage rate of shares on their posts.
Table 3
Average Shares on Posts by Page
Depending on one’s own filter bubble, the size of pro-Trump networks might come as a
surprise. To some media pundits, Trump rode to the White House on a wave of fringe support
(Coppins, 2015) – but that would be a mistake, as analysis of the pro-Trump Facebook Page Like
networks shows.
Each of the pro-Trump pages Facebook Page Like networks were added to one
visualisation using Gephi, which amounted to a total of 5416 nodes with 100,208 edges between
them. To put that into perspective, similar data pulls were made on two media page groups. The
three pro-Trump pages had 16.3 times more nodes and 55.86 times more edges than the liberal-
leaning media group, and 6.45 times more nodes and 55.86 times more edges than the
conservative-leaning media group.
0 100 200 300 400 500 600 700 800
Citizens for Trump
Eagle Rising
Wake up & Reclaim America
Looking at the three pro-Trump pages separately, each network contains a considerable
percentage of pages that have self-categorized on Facebook as “Community”, but also “Public
Figure”, “Politician” and some form of “News/Media” (See Tables 3, 4, and 5).
Tables 4, 5, and 6
Facebook Page Categories Selected by Pages within Pro-Trump Page-Like Network
Public Figure
News/Media Website
Political Organization
Media/News Company
Non-Profit Organization
Community Organization
News Personality
0% 5% 10% 15% 20% 25% 30%
Citizens For Trump
The pro-Trump network was then analysed using Gephi (Figure 1). This included running
the ForceAtlas2, a force-directed layout to transform the network into a map. Additional
statistical analysis was conducted, using Modularity, which helps identify the various
News/Media Website
Media/News Company
Non-Profit Organization
Public Figure
Government Official
News Personality
0% 5% 10% 15% 20% 25% 30%
Eagle Rising
Non-Profit Organization
Political Organization
Media/News Company
News/Media Website
Public Figure
Community Organization
0% 5% 10% 15% 20% 25% 30%
Wake Up & Reclaim America
communities within a network, marked in the data visualization below by colours. The pro-
Trump network wasn’t just bigger in comparison; it was also more closely integrated between
pages with an Average Weighted Degree of 18.502 compared to that of the conservative-leaning
media group at 9.01 or the liberal-leaning at 5.404 (the higher the number, the greater the
average number of edges that touch a node in the network).
Figure 1. Three Pro-Trump Facebook Page Like networks analysed using Gephi
Pages liking each other demonstrate a possible channel for the spread of information. To
investigate further, Netvizz was used to pull all posts made by each page from 7 October to 7
November 2016, a month before the election. These posts where analysed using Excel to count
the mentions of specific terms (such as Clinton, Trump, and Wikileaks), how many posts were
shared from other accounts, and what web domains were shared to the page, for example. The
same investigative process was then applied to analysing the two media page groups.
Around one third of the posts made by Wake Up & Reclaim America (34.1%) and
Citizens for Trump (28.7%) were shares from other Facebook accounts or pages, indicating
community-like behaviour on these two pages.
Table 7
Number of Posts Shared from Other Facebook Pages or Accounts
Some pages such as Occupy Libtards13 enjoyed repeated shares to Wake Up & Reclaim
America, including The Deplorables.14 This Facebook group has 472,297 Members (as of 18
April 2017) and takes its name from a comment made by Hillary Clinton during the election
about Trump supporters.
These pro-Trump pages are not operating in isolation. Of note as bigger nodes in the pro-
Trump Facebook Page Like network visualisation are Fox News, Sean Hannity, The Blaze, and
13 See:
14 See:
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
Drudge Report
Glenn Beck
Sean Hannity
The Blayze
Citizens for Trump
Eagle Rising
Wake up & Reclaim America
Glenn Beck (see the darker orange community in the upper left of the network) – not to mention
the NRA Institute for Legislative Action and The Heritage Foundation (Figure 3).
Figure 3. Zoomed in screenshot of pro-Trump Facebook Page Like network using Gephi
Beyond the official political campaign Facebook pages, hundreds if not thousands of
other pages pumped content supporting Trump to sympathetic users of that social network.
Indeed, within the Wake Up & Reclaim America Facebook Page Like network, 207 page names
contain the word “Trump” – many more that are pro-Trump do not, making them much more
difficult to track. Together these Facebook pages support each other with reciprocal Page Likes
and sharing of posts, while also mobilizing users to not just spread the message but also support
Trump. In so doing, these online communities are also tapping into bigger organisations, such as
media outlets, lobby groups, and think tanks – hinting at a much more systemic participatory
propaganda effort.
How did pro-Trump Facebook pages engage with media outlets?
The pro-Trump Facebook Pages certainly followed right-leaning media outlets, as can be
identified in the Page Like networks visualised above and featuring Fox News and Sean Hannity,
among others.
The liberal-leaning media group, visualised in Figure 4, comprised seven almost entirely
independent communities. The visualisation below uses Gephi’s stronger gravity function to
keep the communities closer together for ease of viewing; however, they are not linked so
closely in reality. What’s more, the Facebook pages tend to be grouped into ‘ego networks’,
meaning any given media outlet tends to only like pages related to that network, such as its own
TV shows or journalists.
Figure 4. Left-leaning media Facebook Page Like networks using Gephi and stronger gravity to
make the visualization easier to read
The conservative-leaning media group is quite different (Figure 5). The massive Infowars
community dominates the visualisation, represented here below by the large yellow section,
running into the Alex Jones network in blue, which comes with it. While nodes connect the
Infowars monolith to Fox, the key connector page is Judge Andrew Napolitano. This is
interesting in itself, as in past analysis of media Facebook Page Like networks, Fox stood out
from outlets such as BBC for its connecting to personalities, both their own journalists as well as
U.S. politicians, suggesting that some media outlets aren’t just covering the news, but engaging
directly with the subjects making the news (Wanless, 2015). This form of engagement could be
considered alarming, if the notion of impartial news is accepted as crucial to a functioning
Figure 5. Right-leaning media Facebook Page Like networks using Gephi and stronger gravity to
make the visualization easier to read
When these two media groups are combined with the pro-Trump network (Figure 6), the
liberal-leaning outlets become islands unto themselves almost entirely disconnected (the blue
communities at the bottom left), while the conservative-leaning media are absorbed into the
overall community, and as noted above, in some cases becoming influential nodes.
Figure 6. All Facebook Page Like networks combined using Gephi
In short, the conservative-leaning media network is more of an ecosystem that stretches
beyond news outlet borders, blending into each other and pages beyond just media and
journalists, into communities.
Pro-Trump Pages in a Participatory Propaganda Model
While the analysis presented above is based on a very limited number of pages, the
degree of engagement and inter-connectivity, both inside the network and with supportive media,
demonstrate the existence of a systematic and coordinated attempt to influence the U.S. voters to
support the Trump campaign. All but one of the tactics identified in the participatory propaganda
model were used by Trump supporters to achieve this goal, including sharing provocative content
(fake news, memes and data leaks), feeding such content into an echo chamber, reposting the
same content, encouraging followers to do the same, and connecting with media and larger
organisations supportive of Trump. The only element missing was hyper-targeted audience
analysis, as this activity is typically conducted through in-house research during a campaign and
is not traceable through open sources. However, Cambridge Analytica has openly claimed to
have used such tactics for the Trump campaign. (Nix, 2016)
Conclusion: Participatory Propaganda in Liberal Democracies
As demonstrated in this paper, the organized deployment of various emerging
technological and manipulative techniques in a digital era facilitates the emergence of an
interactive form of engagement online where followers (target audience) are drawn into
participating in the creation and spread of persuasive messaging. The example of the Trump 2016
presidential election campaign was used to demonstrate how these new tactics were deployed in
combination with traditional media coverage to draw a considerable online following. This
follower engagement consitutes a qualitatively more enhanced form of propaganda that is much
more ‘invasive’ in nature – not to mention potentially very dangerous for liberal democracies.
As internet penetration rates in democratic countries surpasses 80% (as in Canada (CIRA,
2016), U.K. (U.K. Office for National Statistics, 2016) and the U.S. (Pew, 2017)), with many
others in tow, nearly half of those populations finished high school before the web was even
invented.15 As of 2015, 21% of American survey respondents indicated they were online “almost
constantly” (Perrin, 2015), and by the end of the first quarter in 2016, the average American was
consuming 10:39 hours (Nielsen, 2016) of media across devices each day. Unlike radio and
television before it, the internet has people constantly connected to information. Americans are at
the vanguard of these changes – and as such are among the most vulnerable populations to
information warfare, be it in the form of participatory propaganda, social engineering or cyber-
With such levels of exposure to a constant barrage of information, the ability of any one
individual to discern its veracity or relevancy in a broader context of daily life is constantly
challenged. Furthermore, the effects of continuous online exposure on individual mental health
or how such activities shape perceptions are still too poorly understood, and as such, are not yet
part of mainstream knowledge or incorporated into national education curriculums at the level
required to cope. The negative and long-lasting repercussions of such limited understanding are
perhaps nowhere as serious as in national politics.
In 2014, the World Economic Forum listed “the spread of misinformation online” as one
of the top 10 trends facing the world (WEF, 2014). By 2016, Reporters Without Borders declared
15 Similar models of participatory propaganda have been identified through subsequent research on the
2017 U.K. general election ( and Canadian
political Facebook pages (
that we “have reached the age of post-truth, propaganda, and suppression of freedoms –
especially in democracies” (2016). As demonstrated above, modern propagandists have a
considerable arsenal of methods at their disposal to manipulate populations, influence their
opinions or engage them in active propagation of the desired content that go well beyond the
creation and distribution of ‘fake news’ alone. What perhaps stands out most in this participatory
propaganda model is its perpetuation. Through the use of online communities such participatory
propaganda campaigns run as long as the cause driving it matters to its members – or rather,
those administrating such groups are able to produce content that engages and provokes
followers. Finding ways to identify and measure engagement within these networks should be a
priority for those studying liberal democracies.
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... These findings demonstrated that of the seven identified steps in the Participatory Propaganda model at least four (provocative content, echo chambers, amplification through bots and algorithms, and encouragement to act) were present in campaigns supporting parties on both the Left and Right of the political spectrum.Canada: Similar analysis was carried out on 20 Canadian Facebook pages, representing both the political Left and Right evenly(Wanless, 2017b). The period analysed(17 June to 16 July 2017) was roughly about two years prior to the federal elections scheduled for October 2019 and was chosen to gauge whether some of the Participatory Propaganda steps may be identifiable in the early political activity online. ...
Revised Chapter for Sage Handbook on Propaganda: Propaganda is changing in a Digital Age. What once was a top-down effort to the masses has through the internet become a participatory affair. As people increasingly "plug-in" to online services, a wealth of personal data aggregated by internet giants facilitates the creation and distribution of tailored provocative messaging, which savvy propagandists then push through online communities to unsuspecting target audiences who help spread persuasive content further. In this dynamic information environment, audiences are no longer passive consumers of persuasive content. Instead, they are active agents who participate in its creation, spread and amplification, inadvertently furthering the agenda of propagandists whose messaging resonates with their world view. Propagandists achieve this through behavioural advertising, manipulating internet algorithms, targeting and provoking online echo chambers and communities, and winning traditional media coverage. Often such efforts blur the lines between what is real and what isn't, when staged activities are obfuscated through astroturfing or botnet amplification to look like an authentic engagement by ordinary users. These methods, alongside the pervasiveness of modern communications in our lives, create ample opportunities for skilled propagandists to set agendas for and influence national political dynamics or policy choices. This chapter explores the emergence of participatory propaganda, drawing from a model first identified during the US 2016 presidential election and subsequently found in online political activity in the UK and Canada using social network and content analysis. 2
... Пропаганда с таким включенным участием пользователей направлена не столько на то, чтобы продвигать новое, а скорее подтверждать то, что уже было заявлено [6]. Это ...
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The first to shoot today is cognitive "troops"
... representing both the political Left and Right evenly (Wanless, 2017b). The period analysed (17 June to 16 July 2017) was roughly about two years prior to the federal elections scheduled for October 2019 and was chosen to gauge whether some of the Participatory Propaganda steps may be identifiable in the early political activity online. ...
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Propaganda is changing in a Digital Age. What once was a top-down effort to the masses has through the internet become a participatory affair. As people increasingly “plug-in” to online services, a wealth of personal data aggregated by internet giants facilitates the creation and distribution of tailored provocative messaging, which savvy propagandists then push through online communities to unsuspecting target audiences who help spread persuasive content further. In this dynamic information environment, audiences are no longer passive consumers of persuasive content. Instead, they are active agents who participate in its creation, spread and amplification, inadvertently furthering the agenda of propagandists whose messaging resonates with their world view. Propagandists achieve this through behavioural advertising, manipulating internet algorithms, targeting and provoking online echo chambers and communities, and winning traditional media coverage. Often such efforts blur the lines between what is real and what isn’t, when staged activities are obfuscated through astroturfing or botnet amplification to look like an authentic engagement by ordinary users. These methods, alongside the pervasiveness of modern communications in our lives, create ample opportunities for skilled propagandists to set agendas for and influence national political dynamics or policy choices. This chapter explores the emergence of participatory propaganda, drawing from a model first identified during the US 2016 presidential election and subsequently found in online political activity in the UK and Canada using social network and content analysis.
What is the future of political propaganda? Is the future ‘now’? When information warfare in Ukraine was made public, discussion about recent forms of propaganda dissemination appeared. A new period of propaganda emerged when human-controlled online accounts (so-called trolls) began manipulating online information. After allegations of Russian interference in the 2016 presidential elections in the United States, upgraded trolls—robotised accounts—gained attention. Shortly after that, the Cambridge Analytica scandal and its micro-targeted political campaigns based on data mining for political authorities worldwide emphasised the extent to which modern technologies can influence political decision-making. Moreover, we are now reading about the threat of the so-called deepfakes and their ability to perfectly deceive a target audience. In this chapter, we present current online propaganda tools in the context of the different information environment, examples of its use, and the possible threats of online propaganda in the future.
We conducted a mixed-method, interpretative analysis of an online, cross-platform disinformation campaign targeting the White Helmets, a rescue group operating in rebel-held areas of Syria that have become the subject of a persistent effort of delegitimization. This research helps to conceptualize what a disinformation campaign is and how it works. Based on what we learned from this case study, we conclude that a comprehensive understanding of disinformation requires accounting for the spread of content across platforms and that social media platforms should increase collaboration to detect and characterize disinformation campaigns.
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The 2016 US Presidential Election brought considerable attention to the phenomenon of “fake news”: entirely fabricated and often partisan content that is presented as factual. Here we demonstrate one mechanism that contributes to the believability of fake news: fluency via prior exposure. Using actual fake news headlines presented as they were seen on Facebook, we show that even a single exposure increases subsequent perceptions of accuracy, both within the same session and after a week. Moreover, this “illusory truth effect” for fake news headlines occurs despite a low level of overall believability, and even when the stories are labeled as contested by fact checkers or are inconsistent with the reader’s political ideology. These results suggest that social media platforms help to incubate belief in blatantly false news stories, and that tagging such stories as disputed is not an effective solution to this problem. Interestingly, however, we also find that prior exposure does not impact entirely implausible statements (e.g., “The Earth is a perfect square”). These observations indicate that although extreme implausibility is a boundary condition of the illusory truth effect, only a small degree of potential plausibility is sufficient for repetition to increase perceived accuracy. As a consequence, the scope and impact of repetition on beliefs is greater than previously assumed.
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The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15--where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., "echo chambers." Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades' size.
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Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. Here we report the results of five relevant double-blind, randomized controlled experiments, using a total of 4,556 undecided voters representing diverse demographic characteristics of the voting populations of the United States and India. The fifth experiment is especially notable in that it was conducted with eligible voters throughout India in the midst of India's 2014 Lok Sabha elections just before the final votes were cast. The results of these experiments demonstrate that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) search ranking bias can be masked so that people show no awareness of the manipulation. We call this type of influence, which might be applicable to a variety of attitudes and beliefs, the search engine manipulation effect. Given that many elections are won by small margins, our results suggest that a search engine company has the power to influence the results of a substantial number of elections with impunity. The impact of such manipulations would be especially large in countries dominated by a single search engine company.
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Polls show a strong decline in public trust of traditional news outlets; however, social media offers new avenues for receiving news content. This experiment used the Facebook API to manipulate whether a news story appeared to have been posted on Facebook by one of the respondent's real-life Facebook friends. Results show that social media recommendations improve levels of media trust, and also make people want to follow more news from that particular media outlet in the future. Moreover, these effects are amplified when the real-life friend sharing the story on social media is perceived as an opinion leader. Implications for democracy and the news business are discussed.
Following the 2016 US presidential election, many have expressed concern about the effects of false stories ("fake news"), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: 1) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their "most important" source; 2) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; 3) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and 4) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.
Social media have been extensively praised for increasing democratic discussion on social issues related to policy and politics. However, what happens when this powerful communication tools are exploited to manipulate online discussion, to change the public perception of political entities, or even to try affecting the outcome of political elections? In this study we investigated how the presence of social media bots, algorithmically driven entities that on the surface appear as legitimate users, affect political discussion around the 2016 U.S. Presidential election. By leveraging state-of-the-art social bot detection algorithms, we uncovered a large fraction of user population that may not be human, accounting for a significant portion of generated content (about one-fifth of the entire conversation). We inferred political partisanships from hashtag adoption, for both humans and bots, and studied spatio-temporal communication, political support dynamics, and influence mechanisms by discovering the level of network embeddedness of the bots. Our findings suggest that the presence of social media bots can indeed negatively affect democratic political discussion rather than improving it, which in turn can potentially alter public opinion and endanger the integrity of the Presidential election. © 2016, Alessandro Bessi and Emilio Ferrara. All Rights Reserved.
All PR, whether for charities or arms manufacturers, is weak propaganda. Though it has its undeniable benefits (it grabs attention and helps circulate more information), it also has costs (such as selective messaging). This extensively revised edition of a classic text fully investigates PR, updating and expanding earlier arguments and building upon the successful first edition with new thoughts, data and evidence. Thought-provoking and stimulating, Rethinking Public Relations 2nd Edition challenges conventional PR wisdom. It develops the accepted thinking on the most important question facing PR - its relationship with democracy - and finds a balance of advantages and disadvantages which leave a residue of concern. It tackles topical issues such as: PR as a form of propaganda which flourishes in a democracy; the connections between PR and journalism; the media, promotions culture and persuasion. Designed to appeal to final year undergraduates, postgraduates and researchers studying public relations, media and communications studies, this book explores the most important relationship PR has - the connection with democracy - and asks what benefits or costs it brings to politics, markets and the media.
Right-wing populist parties are thriving across Europe. Their success is usually attributed to demand-side voter factors and supply-side factors explaining differences in success between countries and parties, such as the role of the media. This study focuses on the interplay of these factors and adds to the literature on media and political populism by (1) its individual-level focus, accounting for indirect effects, and (2) the use of an experimental design employing a party cue and two right-wing populist cues: an immigrant cue and an anti-politics cue. The authors find effects of certain cues on key attitudes driving right-wing populist support—anti-immigrant attitudes and political cynicism. Furthermore, through these attitudes, the cues indirectly affect probability to vote for such a party.