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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 online 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 perceived 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 identified 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., am 28.06.2018, 16:53:11
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208 Studies in Communication and Media, 7. Jg., 2/2018, S. 208–230, DOI: 10.5771/2192-4007-2018-2-208
Studies in Communication and Media
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
Studies in Communication and Media, am 28.06.2018, 16:53:11
Open Access - -
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)
Jörg Haßler (Dr.), Institut für Publizistik, Johannes Gutenberg-Universität Mainz, Jakob-
Welder-Weg 12, 55128 Mainz, Germany; Contact: joerg.hassler(at)
Pablo Jost (M.A.), Institut für Publizistik, Johannes Gutenberg-Universität Mainz, Jakob-
Welder-Weg 12, 55128 Mainz, Germany; Contact: pablo.jost(at)
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)
Marcus Maurer (Prof. Dr.), Institut für Publizistik, Johannes Gutenberg-Universität Mainz,
Jakob-Welder-Weg 12, 55128 Mainz, Germany; Contact: mmaurer(at), am 28.06.2018, 16:53:11
Open Access - -
Popularity cues in online media: Theoretical and methodological
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 identied 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
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 beeinussen. 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 identiziert 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), am 28.06.2018, 16:53:11
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Porten-Cheé/Haßler/Jost/Eilders/Maurer | Popularity cues in online media (Perspectives)
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’ denition 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 dened as popularity cues
that primarily point to user reactions that might either indicate attention and, am 28.06.2018, 16:53:11
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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 inuence their potential effects. However, because
Likes and Shares of social media messages compete with additional social cues
that could inuence why individuals apply popularity cues and whether they are
affected by them, different contexts of reception were considered whenever ap-
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, am 28.06.2018, 16:53:11
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Porten-Cheé/Haßler/Jost/Eilders/Maurer | Popularity cues in online media (Perspectives)
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 identied 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 Leeang (2012) asked
whether the valence of the message inuences 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 identied 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,, am 28.06.2018, 16:53:11
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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 reecting 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 benet from a recipient-oriented perspective (see the call for such an ap-
proach by Haim, Kümpel, & Brosius in this issue)., am 28.06.2018, 16:53:11
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Porten-Cheé/Haßler/Jost/Eilders/Maurer | Popularity cues in online media (Perspectives)
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 inuence 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 benet 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 signicant 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., am 28.06.2018, 16:53:11
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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 specic 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 inuence the audience in political terms.
2.2.1 Effects on exposure
Communication research has developed several theoretical approaches to explain
why users prefer specic 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, am 28.06.2018, 16:53:11
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Porten-Cheé/Haßler/Jost/Eilders/Maurer | Popularity cues in online media (Perspectives)
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 reecting 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 satised 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, am 28.06.2018, 16:53:11
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218 Studies in Communication and Media, 7. Jg., 2/2018
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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 afrm 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 specic 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 denition
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, am 28.06.2018, 16:53:11
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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 specic 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-specic.
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 inuenced 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, am 28.06.2018, 16:53:11
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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 conict 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 difculties 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 specic 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, am 28.06.2018, 16:53:11
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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 specic 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 specic 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 inuencing the articulation of popu-
larity helps us to understand what makes sources and messages interesting or
even persuasive. To isolate the factors inuencing 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 inuencing 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 inuence 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, am 28.06.2018, 16:53:11
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the characteristics of popular as well as unpopular tweets, this bivariate approach
cannot be used to analyze more than one inuencing factor. To address the short-
comings of these approaches, third, multivariate analysis can be used to analyze
two or more factors that might simultaneously inuence 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 inuences of other content criteria (see also Haßler, Jost, Maurer,
2016). As this procedure clearly allows to identify the inuence 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, specic 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 inuencing 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, am 28.06.2018, 16:53:11
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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 difcult 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 specic 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 fullled – 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 reect 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:, am 28.06.2018, 16:53:11
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Asking about cognitions and perceptions rst may increase the sensitivity to later
conrm 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 reected 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 benet 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, am 28.06.2018, 16:53:11
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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 specic 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., am 28.06.2018, 16:53:11
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... Interactivity is not only a process that connects political actors and users, but is also a measure of a political message's popularity on SNS (Porten-Chée et al., 2018). ...
... In fact, when the followers of the account of a political actor interact with a post or tweet (i.e. by sharing/retweeting, liking/favouring, or commenting/tweeting), this message gets amplified and distributed across the users' personal networks on the platform as well (Vaccari and Valeriani, 2015). Research has shown that content resonating with the audience and hence potentially becoming popular is preferred by the sender of a message; audiences, conversely, use popularity as a selection criterion to identify with which messages to interact (Porten-Chée et al., 2018). In fact, political actors may, therefore, actively want to produce content that they expect to be well received by their support base, so that their engagement increases the visibility of the content beyond the partisan network (Kelm, 2020). ...
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We investigate user engagement with politicians’ migration discourses on social media. In particular, we study the effects of message framing and support base attitudes on interactions on Facebook and Twitter in five European countries. Enriching automated analysis of social media content with survey data in a multilevel negative binomial regression approach, findings show that migration-related messages tend to elicit more interactions than other kinds of messages. Furthermore, the presence of a security frame in a migration-related message positively relates to user engagement. However, additional analyses suggest that the relevance of these frames differ between different political parties. In fact, a message gets an even higher number of interactions, when the dimension of the migration issue included in those framed messages is perceived more negatively by a party’s support base. The findings have important implications for communication strategies of political actors and the state of migration discourses on social media.
... Third, social media logic also encompasses a stimulation of user activity in form of communication behavior that affects the subsequent flow of information through social media platforms by means of so-called popularity cues, that is, the number of likes and retweets of content (Porten-Cheé et al., 2018). Popularity cues thereby mainly describe positive user reactions and, at least on an aggregated level, suggest the assigned relevance and endorsements of online messages. ...
... On the one hand, they are an indicator of successful communication efforts as there is evidence of an impact of social media engagement on organizational trust (Dessart, 2017). On the other hand, popularity cues can affect the audience's perceptions of as well as the attitudes and behaviors toward social media content (Haim et al., 2018;Porten-Cheé et al., 2018). Research suggests that content with a large user engagement, that is, content that contains stronger popularity cues, is more likely to be clicked, ascribed a higher quality as well as credibility and has a stronger impact to stimulate behavior such as comments or shares (Haim et al., 2018). ...
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Using a neo‐institutional framework, this study investigates how German police use Twitter for their communication. This is relevant, because the police increasingly use social media to bypass the media's gatekeeping function and attain increased agency in communication activities. However, little is known about their different communication strategies and their impact on user engagement. The analysis is based on an automated content analysis of all Tweets (N = 137,771) sent out by the German police in 2019. It identifies different patterns regarding the usage of Twitter between police entities on different levels of governance and in differing types of environments and examines how these patterns translate into different levels of user engagement. We find that German police entities differ in their use of Twitter and that environmental and organizational aspects can explain these differences. Moreover, different patterns of social media usage also lead to differing levels of user engagement. This article is protected by copyright. All rights reserved.
... Being "small," however, does not diminish their importance, as aggregating multiple instances of specific behavior ascribes a monetary value to that behavior (Gerlitz and Helmond, 2013). Despite not capturing emotional or normative aspects of engagement, these popularity cues are "metric information about users' behavior or their evaluations of entities" (Haim et al., 2018: 188) that have the capacity of affecting not only news production but also patterns of consumption among the audience as they often feed into algorithmic recommendation systems that drive news consumption (Porten-Cheé et al., 2018). Moreover, by posting news on social media, news organizations aim to both drive and increase engagement with their content, which, at the same time, will modify audience behavior. ...
... What Schrøder and colleagues propose is that the North/Central European model can further be divided into sub-systems and that within the Nordic system, there are minor, but significant national differences. Surveying these popularity cues highlights the perceived relevance of news items among a population that can be appreciated by both news producers and audiences, potentially affecting both patterns of news production and consumption (Porten-Cheé et al., 2018). At a large-scale and aggregated level, these cues or acts of engagement show Facebook audiences considered worth interacting with and providing patterns of collective behaviors toward news outlets' posts. ...
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Information production, dissemination, and consumption are contingent upon cultural and financial dimensions. This study attempts to find cultures of engagement that reflect how audiences engage with news posts made by either commercial or state-owned news outlets on Facebook. To do so, we collected over a million news posts ( n = 1,173,159) produced by 482 news outlets in three Scandinavian countries (Denmark, Norway, and Sweden) and analyzed over 69 million interactions across three metrics of engagement (i.e. comments, likes, and shares). More concretely, we investigate whether the patterns of engagement follow distinct patterns across national boundaries and type of outlet ownership. While we are skeptical of metrics of engagement as markers of specific cultures of engagement, our results show that there are clear differences in how readers engage with news posts depending on the country of origin and whether they are fully state-owned or private-owned outlets.
... Empirisch zeigt sich, dass Emp fehlungen (Bewertungen) anderer Nutzerinnen und Nutzer die Aufmerk samkeit auf bestimmte Inhalte lenken können (u. a. Knobloch-Westerwick et al., 2005;Porten-Cheé et al., 2018). Der aggregierte Wert von Pro-Stim men zu einem Initial-Vorschlag kann als Hinweis auf die Popularität des Vorschlags interpretiert werden. ...
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This book is dedicated to the dynamics of public deliberation online. Based on a critical examination of the traditional concept of deliberation, it discusses narration, expressions of emotion and humour as deliberative forms of communication in addition to argumentation. In addition to classic counter-argumentation, it considers empathy, constructiveness, reflection and genuine questions to be components of deliberative reciprocity. Empirically, relational content analysis and sequence analysis of two online participation platforms are used to investigate to what extent different forms of communication influence subsequent traditional and inclusive deliberative reciprocity.
... Further, user engagement can increase the credibility of individual messages via a more impersonal peer influence as well. User engagement metrics are often considered as popularity cues (Porten-Cheé et al., 2018) and thereby affect the perceptions of both users (Messing & Westwood, 2014) and journalists (McGregor, 2019) about the public support of different viewpoints and actors. ...
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... Yet, politicians need to be responsive to civil society to gain higher levels of legitimacy. Social media represent certainly one channel through which they can demonstrate their responsiveness to concerns from other users (Porten-Cheé et al., 2018), and also through which politicians can learn about public preoccupations to adapt their agenda (Ennser-Jedenastik et al., 2021). Therefore, in this study, we particularly focus on the effect of politicians' responsiveness on social media in terms of replies and policy issue responsiveness on their political success. ...
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... Interactive engagement metrics Popularity cues, such as the numbers of likes, comments, and retweets, can serve as an indicator of the success of the media's agenda-setting, framing, and propaganda strategies. These popularity cues have further consequences: they can be used to recommend content on social media platforms and thus impact users' media diets, and they can act as heuristics for people trying to decide what media content is credible, accurate, and important (Haim et al., 2018;Porten-Cheé et al., 2018). Consistent with the idea that the Twitter public sphere is more globallyoriented (especially Western-oriented), independent media posts receive more engagement on Twitter than state-affiliated posts (289.0 vs. 52.7 likes and 69.6 vs. 13.5 retweets, respectively). ...
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In this report, we describe a new data set called VoynaSlov which contains 21M+ Russian-language social media activities (i.e. tweets, posts, comments) made by Russian media outlets and by the general public during the time of war between Ukraine and Russia. We scraped the data from two major platforms that are widely used in Russia: Twitter and VKontakte (VK), a Russian social media platform based in Saint Petersburg commonly referred to as "Russian Facebook". We provide descriptions of our data collection process and data statistics that compare state-affiliated and independent Russian media, and also the two platforms, VK and Twitter. The main differences that distinguish our data from previously released data related to the ongoing war are its focus on Russian media and consideration of state-affiliation as well as the inclusion of data from VK, which is more suitable than Twitter for understanding Russian public sentiment considering its wide use within Russia. We hope our data set can facilitate future research on information warfare and ultimately enable the reduction and prevention of disinformation and opinion manipulation campaigns. The data set is available at and will be regularly updated as we continuously collect more data.
... Pageviews, also referred to as "clicks" or "hits," are recorded whenever a page is viewed by the news reader by any method such as clicking on a link, typing in a URL or refreshing a page (Cherubini and Nielsen 2016;Petre 2015). These metrics have been taken at face value by both researchers and media professionals alike as primary measure of popularity or preference (Porten-Ch ee et al. 2018;Schaudt and Carpenter 2009;Tenenboim and Cohen 2015). For instance, most-viewed lists often seem to be dominated by entertainment, crime and sports news, indicating that news users prefer softer news over news about public affairs (Boczkowski and Peer 2011;Tenenboim and Cohen 2015;Tewksbury 2003). ...
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The contemporary high-choice media environment, characterized by information abundance, makes it increasingly difficult for media outlets to capture audience attention. This concern is particularly pressing for social media, and more specifically for Facebook. Because user engagement is a crucial input factor for the algorithm, fears have risen that journalistic content on digital news media and especially on social media is becoming softer to help adjust to news consumer’s interests. A content analysis was conducted on four consecutive weeks of all news items published online by five market-leading Belgian media outlets (N = 10,579) in order to analyse whether the news supply is adapted to “what the metrics say” and, subsequently, to what extent that metric data is used to promote a “softer” supply of news on Facebook. To measure audience engagement, we used unique metrics provided by the news organizations themselves. The results show that audience metrics support and enhance news softening on the Facebook pages of mainstream media outlets.
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Zusammenfassung Der Beitrag fragt nach strukturellen Veränderungen der politischen Kommunikation, die sich als Folge der Digitalisierung ergeben. Dabei wird eine regelorientierte und institutionalistische Perspektive eingenommen: Digitale Kommunikationsmedien wie Social-Media-Plattformen weisen eigene institutionelle Logiken auf und beeinflussen so die Regeln, nach denen politische Kommunikation stattfindet. Zur Begründung dieser These wird der Begriff Digitalisierung zunächst in technische Möglichkeit und soziale Realisierung unterschieden. Politische Kommunikation wird als Vermittlungsprozess betrachtet. Neben die Selbstvermittlung durch politische Akteure und die Fremdvermittlung durch journalistisch-redaktionelle Medien tritt mit digitalen Kommunikationsmedien ein neuer Typ in den Vordergrund, die automatisiert algorithmische Vermittlung. Aus diesen Unterscheidungen ergeben sich mehrere Paradoxien, die für eine Betrachtung der institutionellen Folgen relevant sind: Digitalisierung senkt die Kosten der Kommunikation und ermöglicht ein Mehr an publizierten Mitteilungen, erschwert jedoch zugleich die Chance gesellschaftlicher Wahrnehmung und gelingender Kommunikation. Durch die automatisiert algorithmische Vermittlung können Akteure ihre Botschaften in höherer Auflösung an spezifische Zielgruppen richten und sich mit ihnen verbinden, die digitalen Formen der Konnektivität erschweren jedoch die für demokratische Prozesse notwendige Repräsentanz und Zurechenbarkeit von Mitteilungen an politische Akteure. Technisch ermöglichte und sozial eingeforderte Transparenz geht mit der Bemühung von politischen Organisationen einher, das eigene Handeln zu verdecken oder zu verschleiern. Digitalisierung und die automatisiert algorithmische Vermittlung führen damit sowohl zu neuen Sichtbarkeiten als auch zu neuen Unsichtbarkeiten des Politischen.
Der vorliegende Beitrag bietet einen Überblick über die Kernkonzepte von Partizipation durch Diskurs und über wesentliche empirische Befunde und nimmt eine kommunikationswissenschaftliche Perspektive ein. Dazu werden Nutzerkommentare zunächst öffentlichkeitstheoretisch eingeordnet. Dann werden der Forschungsstand zu Akteuren, Inhalt und diskursiver Qualität von Nutzerkommentaren auf Nachrichten-Websites, Social Networking Sites und in Online-Partizipationsverfahren subsumiert, Gemeinsamkeiten und Unterschiede zwischen den Plattformen identifiziert und Leerstellen in der Forschung markiert.
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This study investigates the relevance of verbal and visual communication in shaping impressions of candidates among involved and uninvolved viewers of a televised debate. It combines a quantitative second-by-second content analysis of a debate with a CRM analysis of viewers' immediate impressions. In order to test the impact of involvement on the importance of the verbal and the visual channel, viewers with low, medium, and high involvement were compared. As assumed by two-process models of information processing like the ELM, low involvement viewers relied on visual elements to a greater extent than high involvement viewers. However, the impact of the verbal channel was much stronger across all levels of involvement.
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This article provides a review of scientific, peer-reviewed articles that examine the relationship between news sharing and social media in the period from 2004 to 2014. A total of 461 articles were obtained following a literature search in two databases (Communication & Mass Media Complete [CMMC] and ACM), out of which 109 were deemed relevant based on the study’s inclusion criteria. In order to identify general tendencies and to uncover nuanced findings, news sharing research was analyzed both quantitatively and qualitatively. Three central areas of research—news sharing users, content, and networks—were identified and systematically reviewed. In the central concluding section, the results of the review are used to provide a critical diagnosis of current research and suggestions on how to move forward in news sharing research.
People increasingly visit online news sites not directly, but by following links on social network sites. Drawing on news value theory and integrating theories about online identities and self-representation, we develop a concept of shareworthiness, with which we seek to understand how the number of shares an article receives on such sites can be predicted. Findings suggest that traditional criteria of newsworthiness indeed play a role in predicting the number of shares, and that further development of a theory of shareworthiness based on the foundations of newsworthiness can offer fruitful insights in news dissemination processes.
Over the last several years political actors worldwide have begun harnessing the digital power of social bots - software programs designed to mimic human social media users on platforms like Facebook, Twitter, and Reddit. Increasingly, politicians, militaries, and government-contracted firms use these automated actors in online attempts to manipulate public opinion and disrupt organizational communication. Politicized social bots - here 'political bots' - are used to massively boost politicians' follower levels on social media sites in attempts to generate false impressions of popularity. They are programmed to actively and automatically flood news streams with spam during political crises, elections, and conflicts in order to interrupt the efforts of activists and political dissidents who publicize and organize online. They are used by regimes to send out sophisticated computational propaganda. This paper conducts a content analysis of available media articles on political bots in order to build an event dataset of global political bot deployment that codes for usage, capability, and history. This information is then analyzed, generating a global outline of this phenomenon. This outline seeks to explain the variety of political bot-oriented strategies and presents details crucial to building understandings of these automated software actors in the humanities, social and computer sciences.
In this study we conceptualize cues in social media that require a single click (e.g., Likes, Favorites) as paralinguistic digital affordances (PDAs). Why do people use PDAs and how do they interpret them when they are the recipient? Through focus groups (N = 25) and interviews (N = 26) we address these research questions within a uses and gratifications framework. Using adaptive structuration theory as a lens for analysis, we examine both faithful and ironic uses of PDAs, finding they contribute more than phatic communication and may indicate just as much about the relationship between sender and receiver as they do content.
Die Entwicklung der Mediennutzung in Deutschland ist ungebrochen und scheint permanent zuzunehmen (vgl. van Eimeren/Ridder 2011). Betrachtet man die Zunahme differenzierter, dann sind es in erster Linie der audiovisuelle Bereich und Angebote im Internet, deren Nutzung zunimmt. Vor allem Videoplattformen wie YouTube und Social Network Sites (SNS) wie Facebook spielen in der Internetnutzung Heranwachsender eine zentrale Rolle (vgl. Frees/van Eimeren, 2011: 354, Wagner/Brüggen/Gebel 2009) und werden nicht nur zur Unterhaltung, sondern zunehmend auch für die tagesaktuelle Information genutzt (vgl. Busemann/Gscheidle 2011). Gerade in der Gruppe der 14-19 Jährigen ist seit einigen Jahren ein deutlicher Rückgang der Fernseh- und Radionutzung zu beobachten, die offenbar immer stärker durch die Nutzung von Internetangeboten substituiert wird (vgl. van Eimeren/Ridder 2011).
The present study sheds light on the nature of the multi-dimensional aspects of news consumption by focusing on three different news-related activities on online social networking services (SNSs): news reading, news posting, and news endorsing. Borrowing from the literature on uses and gratifications theory, as well as media attendance theory and the concept of a technology cluster, the study investigated why people consume news differently on SNSs. The results show that each type of news activity may derive from different kinds of motivations, media habits and technology clusters. For example, the motivation of “getting recognition” was found to be an important driving force for news posting, while it was not a significant predictor of news reading and news endorsing. On the other hand, the “entertainment” motivation was revealed to be positively associated with news reading and news endorsing, while it was not with news posting. In addition, those who have an internet-based news repertoire were more likely to participate in news activities on SNSs and those who have many mobile devices were found to participate in news reading more frequently. The study was conducted using a national online survey.
This study examined the joint effect of message and personality attributes on online news sharing. In two experiments (N = 270, N = 275), readers indicated their likelihood to share news representing two content domains and three informational utility dimensions. A moderated mediation path analysis was used. On average, news consumers shared news containing informational utility. Opinion leaders shared news irrespective of informational utility because they discerned informational utility in news that, objectively speaking, lacked such utility. In one experiment, opinion leaders also were more likely than nonleaders to share news perceived to contain informational utility.