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Social Media Information Environments and Their Implications for the Uses and Effects of News: The PINGS Framework



Social media have become a central source for news and current affairs information. This article focuses on the overarching attributes that shape how people come in contact with news, engage with news, and are affected by news on social media. Although all social media are different and change constantly, news experiences on these platforms can consistently be characterized as personalized, incidental, non-exclusive, as well as granularized and social (PINGS). Accordingly, this article introduces the PINGS framework, which acts as a systematization of social media news experiences and can be used to map key opportunities and challenges of using news across various social media platforms. In addition to presenting the framework components, the article also discusses how researchers can investigate PINGS in empirical studies.
Social media have become a central source for news and current affairs information. This article
focuses on the overarching attributes that shape how people come in contact with news, engage
with news, and are affected by news on social media. Although all social media are different and
constantly change, news experiences on these platforms can consistently be characterized as
personalized, incidental, non-exclusive, as well as granularized and social. Accordingly, this
article introduces the PINGS framework, which acts as a systematization of social media news
experiences and can be used to map key opportunities and challenges of using news across
various social media platforms. In addition to presenting the framework components, the article
also discusses how researchers can investigate personalization, incidentalness, non-exclusivity,
granularity, and sociality in empirical studies.
Keywords: social media, social network sites, online news, political information,
incidental news exposure, high-choice media environment, news media use
This article has been accepted for publication in Communication Theory
(published by Oxford University Press).
Social Media Information Environments and Their Implications for the Uses and Effects of
News: The PINGS Framework
Social media have become an influential player in our news landscape. Across different
countries around the globe, platforms such as Facebook, Twitter, or Instagram are now a central
source for current affairs information and news (Newman et al., 2020). Although the popularity
of specific social media platforms has fluctuated over time—and will likely continue to do so
(see also Bayer et al., 2020)—it can be assumed that the basic practice of turning to social media
for information-related needs is unlikely to diminish any time soon. Users particularly value the
convenience and speed of updates on social media as well as the simplicity of accessing a variety
of sources in one place (see, for example, Shearer & Matsa, 2018, p. 8; Stark et al., 2017, pp.
119–121). Moreover, especially young users seem to appreciate the fact that they can
simultaneously communicate with friends or family and, as a byproduct, stay on top about what
is going on outside their immediate social circle through engaging with current affairs
information (e.g., Bergström & Belfrage, 2018; Boczkowski et al., 2018). But engaging with
news on social media also seems to affect the very process of using news. Research has shown
that news use has become less intentional, shorter in duration, and more fragmented, which also
affects the processing and effects of current affairs information (e.g., Costera Meijer & Groot
Kormelink, 2015; Gil de Zúñiga & Diehl, 2019).
The relevance of social media for informational purposes challenges us to think about the
overarching attributes that shape how people come in contact with news, engage with news, and
are affected by news. While there already is a plethora of research that addresses (parts of) these
issues empirically, theoretical assessments of the changes that social media information
environments have brought about the use of news are sparse and often focused on selected social
media platforms. Moreover, extant theoretical frameworks have mostly addressed specific
albeit highly relevantareas in this domain such as the (changing) role of curating actors and
gatekeepers (Soffer, 2019; Thorson & Wells, 2016) or audiences’ news repertoires (Peters &
Schrøder, 2018). However, what is largely missing is a broad view of what characterizes news
experiences in social media environments and how this affects the uses and effects of news.
Although all social media are different and constantly change, five overarching characteristics
shape news experiences and are likely to endure even if Facebook, Twitter, or other specific
platforms lose their appeal: News experiences on social media are personalized, incidental, non-
exclusive, as well as granularized and social. Accordingly, in this article, I propose the PINGS
framework, which is not only a systematization of social media news experiences but can also be
used to map and assess key opportunities and challenges of using news via social media. For this
purpose, the framework highlights the conditions under which news is encountered, used, and
disseminated today, while acknowledging that none of the characteristics are positive or negative
per se (i.e., personalization is not inherently ‘bad’ and incidentally stumbling upon news not
inherently ‘good’). It also challenges us to think about (new) ways to collect and analyze data on
social media news use.
Using News in Social Media Information Environments: The PINGS Framework
Before proceeding to explicate the framework, it is crucial to define what is (not) meant
by “news” and “social media.” In accordance with prior empirical studies, an inclusive
conceptualization of news is adopted for this article, “which ranges from ‘hard’ news stories
about world or local affairs to ‘softer’ news stories that could include entertainment or sports”
(Vraga, Bode, Smithson, et al., 2016, p. 273). However, while the framework is able to describe
and characterize news experiences across the spectrum from ‘very soft news’ to ‘strong hard
news’ (Lehman-Wilzig & Seletzky, 2010, p. 51), the discussion of effects will often be centered
around hard news due to research on social media news use being heavily focused on political
outcomes (see also Matthes et al., 2020, p. 1034). Still, an attempt is made to explicitly consider
the implications for different types of news. Reflecting extant empirical approaches to studying
news use in social media information environments (e.g., Edgerly & Vraga, 2020b; Kaiser et al.,
2018; Kümpel, 2019a; Schäfer, 2020), the focus is further restricted to news content that
originates from professional journalistic news providers1 but is not necessarily transmitted by
these providers—for example, when a friend is sharing the link to an article by The Guardian.
“News” in a broader sense (i.e., all kinds of previously unknown information) is therefore not the
focus of interest.
Referring to Carr & Hayes (2015; see also Bayer et al., 2020), social media are defined as
disentrained, persistent online channels of masspersonal communication that facilitate interaction
among users. Although the original definition highlights that social media derive “value
primarily from user-generated content” (Carr & Hayes, 2015, p. 49), social media have
undoubtedly become more and more reliant on (external) content that was not created by the
sharing users. Recent social media platforms “are more like news aggregators” (Ellison & boyd,
2013, p. 155) and heavily feature links to external websites or content providers. While social
media news use can be active and goal-directed (e.g., performing a Twitter search for a news
topic, purposely browsing the CNN Instagram page—both of which are possible even without
1 In our current information environment, accompanied by the rise of alternative news media (Holt et al.,
2019) and various types of so-called fake news, “the boundaries between professional and nonprofessional news
content have become increasingly difficult to distinguish” (Tandoc Jr. et al., 2018, p. 2746). In the context of this
article, professional journalistic news providers are normatively defined as institutional actors that are committed to
norms of objectivity, accuracy, and independence, work autonomously and establish truth based on facts (see Deuze
& Witschge, 2018; Lewis, 2019). While this narrow conceptualization certainly does not reflect what (online)
journalism can or does look like in practice (ibid.), it mirrors the news-democracy narrative pervasive in much
empirical research on social media news use (see Edgerly & Vraga, 2020a).
registration), the focus here is on instances where users browse their own feeds in social-media-
typical patterns such as habitual “checking” and laid-back “snacking” (Costera Meijer & Groot
Kormelink, 2015; Schäfer, 2020).
Building on these definitions, the PINGS framework calls attention to the conditions of
coming in contact with news, being attentive to news, and engaging with news on social media
(see Figure 1 for an overview). I will start with a general characterization of the respective
component, accompanied by a discussion of key opportunities and challenges, specifically those
related to the reception of hard news and political outcomes. Following the tradition of Eveland’s
(2003) “mix of attributes” approach, the framework components can be seen as general attributes
of social media news use that are more or less pronounced and intertwined on different social
media platforms (see also Dylko & McCluskey, 2012). This focus on overarching attributes not
only helps researchers to systematically assess the effects of social media news use but also to
extract particularities by comparing the specific configuration of attributes with earlier forms of
(online) news use (Ohme, 2020, p. 105).
Personalization of the News Experience
Whether it is a hashtag-based search on Twitter, discovering a news post in the Facebook
feed, or following a news provider on Instagram—the news experience in social media
information environments is highly personalized. Social media are “fundamentally based on the
idea of customizability” (Dylko, 2016, p. 390), which means that encountering news is
contingent on who users decide to follow, which accounts they have subscribed to, and what
(news) content they frequently read, click on, or disseminate among their network. These
decisions are fed into highly responsive algorithms that influence which content is featured in a
given social media user’s feed. Two types of personalization can be distinguished: (1) Explicit
personalization (Bozdag, 2013; also discussed under terms such as user-driven customization
and personal curation, see Dylko, 2016; Thorson & Wells, 2016) describes instances in which
the social media users themselves take action to customize their information environment, for
example through following journalists or subscribing to news-related pages. (2) Implicit
personalization (Bozdag, 2013; also discussed under terms such as system-driven customization
and algorithmic curation, see Dylko, 2016; Thorson & Wells, 2016), on the other hand, refers to
the idea that platform-specific algorithms infer what the user should be interested in—building
on prior interactions (e.g., clicks, reactions) and the behavior of one’s contacts, but also on more
general factors such as global user trends, or the timeliness of posts. On social media, both types
of personalization work together, creating a constantly changing stream of content that may—or
may notfeature various kinds of news. This observation already highlights the main challenge
associated with personalization, especially in the context of hard news and political information
(see also Kümpel, 2020; Thorson et al., 2019). While “news junkies” (Prior, 2007) that heavily
engage in explicit personalization and follow a lot of news providers or journalists are likely to
encounter more and diverse news, the same cannot be expected for users without an interest in
news, as they are a) unlikely to deliberately follow news accounts on social media (no news-
related explicit personalization), and b) thus unlikely to be targeted with algorithmic
recommendations centering around news (no news-related implicit personalization). Although
these self-reinforcing processes crop up across the range of news types, the implications are
particularly relevant when focusing on the democratic effects of consuming political news (see
also Edgerly & Vraga, 2020a; Matthes et al., 2020).
Of course, the personalization of news experiences is nothing entirely new. Beniger
(1987) points out that personalization efforts could already be observed in the early 19th century
with “innovations as the specialized magazine, targeted mass mailing, neighborhood edition
newspaper, and phone-in radio show” (p. 353). But even if one assumes that traditional media
have, by and large, provided identical (news) content to all consumers, one could argue that the
self-determined selection of a specific TV news program or newspaper in the high-choice media
environment is a form of explicit personalization as well. Along these lines and almost 25 years
ago, Katz (1996) has lamented that TV has lost its role as a central civic space and that “one can
no longer be certain that one is viewing together with everybody else or even anybody else”
(p. 24). However, in comparison with traditional media, being exposed to a personalized
selection of content is hardly a choice on social media. Building on user profiles generated on the
basis of explicitly registered and implicitly determined preferences, social media architectures
are designed to sustain people’s attention, thus striving “to show news that is interesting to users”
(Kozyreva et al., 2020, p. 115). Accordingly, personalization is a key feature of the news
experience in social media environments, unparalleled by any form of personalization in both
traditional and ‘non-social’ online news media.
Incidentalness of the News Experience
In addition to being highly personalized, the news experience in social media information
environments can generally be described as incidental. This framework component strongly
builds on the idea of incidental news exposure (INE), which has received renewed attention with
the increasing use of social media for news. It was both defined as users encountering current
affairs information “while they are not consciously looking for it” (Ahmadi & Wohn, 2018, p. 2)
as well as a secondary activity, “something which accompanies a major activity, often as a by-
product of pursuing the latter” (Boczkowski et al., 2018, p. 3524). However, as Karnowski and
colleagues (2017) note, INE is not an online phenomenon and “has been discussed long before
the advent of the Internet” (p. 43). Examples from non-online environments include viewing a
news ticker on public transport screens, seeing the last minutes of a newscast while awaiting
one’s favorite TV show, or noticing a headline while passing a newspaper vending machine. This
type of ‘offline incidentalness,’ however, differs from the one experienced in social media,
which is heavily dependent on the aforementioned processes of implicit and explicit
personalization (see further: Kümpel, 2020; Thorson, 2020).
Focusing on the social media news experience, we can differentiate two levels of
incidentalness: First, encountering news can be conceptualized as an incidental experience when
considering (1) usage motives. According to data from the Reuters Institute Digital News Report
(Newman et al., 2018), only between a fifth and a third of German (22 %), UK (26 %), and US-
American (32 %) online users who claim to use social media for news even follow the page of a
news provider. Thus, while some users may intentionally visit social media to inform themselves
about current events, news does not seem to be something that the average user is actively
looking for (see also Feezell, 2018, p. 484). However, usage motives may very well influence
how users process and engage with (political) news. Building on a survey with adolescents,
Heiss and colleagues (2019) conclude that users “may have to intentionally expose themselves to
political content [on social media] and elaborate on this content in order to increase their political
engagement” (p. 14, see also Matthes et al., 2020).
Second, individual usage motives aside, there is a (2) situational incidentalness: Even
users who have explicitly expressed their interest in being exposed to news once (e.g., by
following a news provider), do not know how many news posts will be featured in their feeds
when they login to their accounts. This is also the key difference between social media and other
online platforms that have been characterized as encouraging INE (e.g., portal sites, sites of
webmail providers, see Tewksbury et al., 2001), as these sites always feature snippets of news.
Consequently, the likelihood for stumbling upon news may differ from one usage episode to
another, even if the explicit personalization of one’s feed allows some degree of control about
this situational incidentalness.
Non-Exclusivity of the News Experience
Closely linked to the incidentalness of the news experience is the fact that news makes up
only one part of the social media information environment (Kümpel, 2019b, p. 168; Matthes et
al., 2020, p. 1037)—and for most users only a small2 one, especially when considering hard
news. While many researchers have described social media as a space in which “political
information mixes with updates about pets and babies” (Bode, 2016, p. 29) or as a context
“where pictures of cats, parties, celebrities and socially oriented updates irregularly but
continuously are being mixed up with news stories” (Bergström & Belfrage, 2018, p. 585), this
non-exclusivity of the news experience and its implications are usually not the focal points of
empirical research. However, to adequately investigate social media news use and its outcomes,
we certainly need to know what the blend of personal social information, entertaining memes,
and political news means for users’ attention towards and engagement with current affairs
information (see also Matthes et al., 2020, pp. 1037–1038).
Building on systematizations of different stages of news exposure (Ohme & Mothes,
2020; Vraga et al., 2019), it is sensible to differentiate three stages of news exposure on social
media: (1) The initial contact with news posts in one’s feed, (2) the attention dedicated to a
specific news post, and (3) actual engagement (i.e., clicking on and further interacting with the
post). Considering the virtually endless number of choices in social media feeds, the question of
2 In January 2018, Facebook CEO Mark Zuckerberg has stated that he expects “news to make up roughly
4% of News Feed” (Zuckerberg, 2018).
which news posts capture users’ attention is of particular importance. Since measuring attention
is methodologically challenging, there are only a handful of studies that have tried to address this
in the context of social media news use (Bode et al., 2017; Ohme & Mothes, 2020; Sülflow et al.,
2019; Vraga, Bode, & Troller-Renfree, 2016). The stream of posts created for these studies,
however, usually does not represent the whole range of content that is available in a typical
social media feed, thus recreating the idea of non-exclusivity only to an extent. Exclusively
focusing on Facebook, the results of the mentioned studies nevertheless offer some insights into
what a mixed, non-exclusive information environment does to people’s attentiveness. Ohme and
Mothes (2020) found that participants with a higher level of political interest dwelled longer on
journalistic news posts than on entertainment posts, reflecting the self-reinforcing effects
described above for the question of who even gets exposed to (political) news on social media.
Similarly, Bode and colleagues (2017) found that people are quite efficient in identifying
political content and subsequently skipping over it if they are not interested. Using the same
dataset, Vraga and colleagues (2016) furthermore show that different post topics allocate
different amounts of attention and that users spent the most time looking at picture posts,
followed by link posts, and status updates. There is, however, still a lot to unpack when it comes
to the non-exclusivity of the news experience: What influences attention to news posts in strictly
(audio-)visual social media such as Instagram? How does the presence of actual personal social
information (e.g., friends announcing their wedding)—that is usually not part of experimental
studies due to ethical and practical concerns—change the attention towards news in a feed?
These and other questions prompted by the PINGS framework require further consideration.
While one might recognize a kind of non-exclusivity when thinking about a typical TV
channel, where news could be preceded by cartoons and followed by a crime drama, the social
media information environment certainly offers a unique mixture of social information,
entertainment, sponsored content, practical advice, and various types of news. As such, non-
exclusivity is another distinctive feature of the news experience in social media.
Granularity of the News Experience
Whereas the non-exclusivity of the news experience primarily refers to the positioning of
news in the broader social media environment, granularity calls attention to the fact that using
news or interacting with news on social media usually happens in relation to single pieces of
content, for example, when clicking on a link to an article by The New York Times on Twitter,
or liking a political image quote on Instagram. Indeed, on social media, news stories can “be
easily separated from their original placement to circulate independently, get rebundled with
other items, or be chopped into free-floating snippets to be shared apart from the whole story”
(Carlson, 2020, p. 236). Schweiger (2017) has labeled this phenomenon ‘granularized news
exposure’ (translated from German “granularisierter Nachrichtenkontakt”), thereby emphasizing
both the dominance of the so-called “snack news” format (e.g., news teasers/headlines or picture
posts, see Schäfer, 2020) as well as the move away from using integrated news services such as
an entire newspaper or even the front page of its online version. Others have used the term
“unbundling” (e.g., Hermida, 2016, p. 89) to highlight how social media have challenged the
idea of consciously curated journalistic products and obviated the need for relying on selected
news providers (see also Carlson, 2020). Looking at the possible effects of this granularized
news experience, findings are somewhat mixed. Although research in the domain of political
news suggests that even single news posts or teasers contain a certain amount of information and
might thus be able to provide users with “a little bit of knowledge” (Anspach et al., 2019; see
also Bode, 2016), substantial knowledge effects require more than skimming over posts (Lee &
Kim, 2017). In addition, even for hard news ‘junkies’ it seems unlikely to get a comprehensive
overview of the latest developments solely from their social media feeds (Schweiger, 2017, p.
82). There is also the threat of users mistaking mere exposure to snack news with being informed
about an issue or event (Leonhard et al., 2020; Schäfer, 2020). Research suggests that this feeling
of being informed could lead to detrimental effects such as perceiving social media as a good
substitute for other news sources (Müller et al., 2016), eventually leading to neglecting non-
personalized and journalistically curated products.
Thinking about news use in more general terms, one might argue that people have always
interacted with single pieces of news content. In fact, there are probably only a few people that
regularly read all the articles in a newspaper or all pieces that are featured on the front page of a
news site. However, as Schweiger (2017) points out, even if one does not read a single article
thoroughly, it is still possible to get a rough overview of the current news situation by skimming
over these journalistically curated products. Through placement and visual presentation, they
also provide their recipients with a sense of meaning and relative importance (see also Carlson,
2020, p. 236). This contextual information is missing in a social media feed, where a front-page
story with big letters and eye-catching pictures is just another post among countless others.
Furthermore, personalization routines and non-exclusivity make it highly unlikely that a typical
user gets a rundown of news events that is comparable to (online) newspapers or TV newscasts.
Sociality of the News Experience
The fifth and last component of the PINGS framework is concerned with the increased
sociality of the news experience, expressed in the inevitable connection of news with various
types of social information and recommendations. Again, highlighting this component as a
particularity of social media information environments is not intended to suggest that ‘old’ forms
of news experiences are unsocial. Being confronted with news and discussing news has always
been a social affair: Whether it is families watching the evening news together or colleagues
discussing breaking news during lunch hour. With regard to the dissemination of news, research
on news diffusion has repeatedly confirmed the key role of interpersonal communication,
particularly when issues are emotionally charged (e.g., Ibrahim et al., 2008). However, on social
media, being confronted with news necessarily means being confronted with social
information—even without direct social interactions. When imagining a social media user
turning to their feed in the middle of the night and being exposed to a news article posted by
their best friend, commented by ten others, and shared by three more, it becomes apparent why
news cannot be unsocial in social media information environments. Even a post that has not
received any likes, comments, or shares ultimately contains social information, namely that the
post—at least at the time of viewing—has not yet provoked any engagement from others.
On social media, social information is located on two levels, with users being
simultaneously exposed to (1) aggregated recommendations such as the number of likes or
shares, and (2) personal recommendations by friends, family, and acquaintances. Looking at the
effects of aggregated recommendations first, a literature review suggests mixed effects of these
“popularity cues” on users’ evaluations and selection behavior, depending both on user
characteristics (e.g., need for cognition, involvement) and contextual factors (e.g., general post
characteristics, see Haim et al., 2018). Crucially, the effects seem to be dependent on implicit or
explicit reference points to enable users to determine whether, for example, 1,000 likes on a
news post are a lot or little (ibid.). Overall, while aggregated recommendations might offer some
guidance for users’ engagement decisions by changing the heuristics people utilize (Messing &
Westwood, 2014, p. 1056), research suggests that personal recommendations carry more weight.
The social contacts in a given users’ social media network not only influence with which news
the user is confronted but also how this piece of information is perceived and interpreted. The
visible behavior of friends surrounding news posts thus acts as another source layer, in addition
to the original media source (Oeldorf-Hirsch & DeVoss, 2020). A number of recent studies show
that this additional layer positively influences news-related selection decisions and information-
seeking behavior on social media—particularly when the friend source is a strong tie, positively
evaluated, and/or perceived as an opinion leader (e.g., Kaiser et al., 2018; Karnowski et al.,
2017; Kümpel, 2019a; Messing & Westwood, 2013; Turcotte et al., 2015).
Considering these findings, personal social information was often described as an
opportunity to motivate users who lack the intrinsic motivation to engage with news content. But
how likely is it—especially outside of experimental settingsthat users uninterested in news
actually receive news recommendations? A recent study on news tagging practices found that
“news junkies are unlikely to tag their uninterested friends in news stories” (Kümpel, 2019a, p.
390), suggesting that personalized/direct news recommendations are only given if the friend is
already perceived as being interested in the topic. The ‘in-principle’ opportunities provided by
personal recommendations thus seem to be limited by users’ actual social media news practices.
However, regardless of the motivational potential of social news recommendations, sociality is,
without a doubt, fundamental to experiencing news in social media information environments.
Measuring and Observing News Use in Social Media Information Environments
The framework components themselves already point to the problems associated with
studying social media news use empirically. As a result of personalization routines, each user is
confronted with a unique and highly dynamic selection of content, constantly changing with
every new login and usage situation. Grossly simplified, with every improvement of a study’s
external validity (i.e., coming as close to natural social media [news] use as possible), its internal
validity is likely to suffer. Given this, it is often inevitable to focus investigations on selected
characteristics of social media information environments. Accordingly, in this section, I aim to
present some ways to shed light on the five framework components in empirical research.
The most natural—albeit laborious and ethically challenging—way to deal with the fact
that news experiences are personalized, is to conduct research that works with people’s own
social media accounts. For example, a combination of naturalistic observations and self-
confrontation interviews offers insights into how social media users navigate their feeds, the
contextual dynamics of their (news) use, as well as the individual considerations that shape
engagement with personalized content (e.g., Kümpel, 2019b). Other options include combining
tracking and survey data (e.g., Möller et al., 2019), or connecting digital trace data with users’
self-reports (e.g., Thorson et al., 2019). Relying on participants’ provision of their Facebook data
archiveincluding information about their Facebook activity, page likes, or advertisement-
related categorizations of their accounts—, Thorson and colleagues (2019) are able to show that
users who are algorithmically classified as interested in news and politics are more likely to be
exposed to news content. Digital trace data might thus be “a fair proxy for what Facebook
‘knows’ about each user’s topical interests” (ibid., p. 11). As most social media platforms now
provide their users with the opportunity to download the information collected about them (“data
download packages,” see Boeschoten et al., 2020), these data can be used to ‘reverse engineer’
personalization routines and processes of algorithmic interest classificationat least to some
degree. Of course, such designs not only require the willingness of research participants, but also
a comprehensive briefing and careful handling of the provided data. Yet another way to uncover
personalization routines without requiring access to real social media accounts is agent-based
testing, a systematic computational data-capturing approach aimed at simulating human behavior
through automated virtual agents. With a focus on Google News, Haim and colleagues (2018)
have created prototypical personas with different sociodemographic characteristics and interests,
simulated keyword-based searches by these personas, and stored all generated results pages. A
comparable approach might be realized in social media environments by setting up differently
behaving personas/accounts and recording the outcome in feed composition or displayed
The mentioned disparities in incidental news exposure on social media are best addressed
with the methods discussed in the previous section (e.g., with large-scale tracking data, see
Scharkow et al., 2020), because they are largely a result of explicit and implicit personalization.
Focusing more closely on the experience of incidentalness (i.e., what [news] content in one’s
feed is perceived as accidental vs. fairly expectable?), mobile (forced) experience sampling
studies might provide a solution (e.g., Karnowski et al., 2017). Similar to Karnowski and
colleagues (2017), researchers could ask participants to log in to their social media accounts and
give information about “the first post that contained news” (ibid., p. 46), specifically asking
about whether this encounter was perceived as expected (e.g., because the user follows the news
provider) or as coincidental in the narrower sense. Such an approach would also be particularly
suitable to uncover the type of situational incidentalness described above.
For ‘regular,’ retrospective survey studies on INE, it might prove fruitful to not simply
ask participants about how often they come across news when they have been going online for
another purpose but to acknowledge that incidental news exposure is more continuous,
depending on previous behaviors and algorithmic interest classification. Accordingly, the
phenomenon might best be reflected by developing multiple indicators that point to a user being
more or less likely to ‘stumble’ upon news in their feed (see also Kümpel, 2020; Thorson, 2020).
To grasp the non-exclusivity of news experiences, researchers might once more consider
working with people’s own social media accounts in observational studies or relying on tracking
data (see above). Furthermore, non-exclusivity seems particularly crucial to consider in
experimental research on social media news use. Given that a) a feed full of news posts is a
rather rare sight for most users, and b) a mixed information environment likely changes the
amount of attention users are willing to give to news, it is advisable to create scenarios in which
news posts are not the only option for engagement (for such an approach see Bode et al., 2017;
Vraga, Bode, & Troller-Renfree, 2016). Additionally, to study the idea of non-exclusivity in an
even broader context than just in the realm of social media, analyses of people’s screenome
defined as the “unique individual record of experiences that constitute psychological and social
life on digital devices with screens” (Reeves et al., 2019, p. 3)—could offer valuable insights.
Such a comprehensive perspective on people’s information ecology is of particular importance,
as it must be assumed that users are not only affected by non-news content in the social media
feed itself, but also by external distractions such as notifications from other apps, incoming calls,
or text messages. Acknowledging that news experiences are in constant competition to other,
oftentimes more entertaining options, should be considered when designing studies on social
media news use. If that is not feasible, the implications of a non-exclusive news environment
should at least be kept in mind when interpreting the results, especially when dealing with
manipulated stimuli.
The granularity of news experiences is probably the component of the framework that is
hardest to investigate adequately. While it is comparatively straightforward to measure the
differential effects of being exposed to just a news teaser/post vs. a full journalistic piece (e.g.,
Lee & Kim, 2017; Schäfer, 2020), such a study design is not really at the heart of what
granularity entails. Questions triggered by this component are rather concerned with how broad
and diverse in content encountered news posts are. One possibility to address these questions is
to use a browser plug-in that automatically collects all posts that are available in a user’s social
media feed (such a plug-in for Facebook is presented in Haim & Nienierza, 2019). To protect the
privacy of the users, the plug-in developed by Haim and Nienierza (2019) only collects public
posts (e.g., from news pages, meme accounts) as well as contextual information such as the
number of popularity cues or the post’s position in the feed. In a subsequent step, the collected
posts can be subjected to content analyses to determine to what kind of news posts participants
were exposed to and whether these offer a comprehensive overview or, on the contrary, just
focus on specialized topics or issues. With regard to news providers and possible platform
differences, it would also be possible to analyze a) which news make it to different social media
at all, and b) whether these are presented and framed differently. From an audience perspective,
even more insights might be generated by an approach similar to Doris Graber’s seminal work
Processing the News (Graber, 1984): Relying on a combination of a news diary, in-depth
interviews, and an analysis of the posts reported in the diary could help to better understand
subjective reactions to social media news posts as well as how people process and make sense of
granularized news encounters.
While non-personalized (e.g., news sharing by fictional individuals) and aggregated
social information (e.g., number of likes on a news post) are easy to manipulate in experimental
studies, working with personalized social information is more challenging. In the past, some
researchers have used the application programming interface (API) of social media platforms to
extract information about participants’ interactions with friends, thus being able to infer tie
strength without relying on self-reported measures and to (semi-)automatically create
personalized stimuli (e.g., Messing & Westwood, 2013; Turcotte et al., 2015). However, in
recent years, API access has become severely restricted, curtailing API-related social media
research. To study the effects of personalized social information without obliging participants to
grant direct access to their accounts, experimental researchers have thus started to come up with
alternative methods to create stimuli featuring the names of participants’ actual contacts. A
popular approach is asking participants to list the names of their (least) close friends (e.g., Kaiser
et al., 2018; Oeldorf-Hirsch & DeVoss, 2020) or—to avoid the problems associated with such
free recall (e.g., predominantly remembering strong ties)—work with task-based name
generators (e.g., Kümpel, 2019a). When conducting observations or using tracking data it is
usually not possible to determine the relationship between a news-sharing friend and the exposed
user without further self-report measures. On the other hand, if researchers are interested in
social influence in more general terms, inferences might also be drawn from network analyses
and patterns of information dissemination (e.g., Garcia et al., 2017).
Platform Differences and the Interplay of the Framework Components
Thus far, the components of the PINGS framework were mainly discussed in isolation
and without explicitly acknowledging the extent to which they are characteristic for different
social media platforms. However, in order to grasp users’ actual experiences with news, it is
important to not just consider the individual attributes but their interconnectedness. Indeed, it is
only in combination that personalization, incidentalness, non-exclusivity, granularity, and
sociality create users’ social media news experiences. For example, whether a user ‘stumbles’
upon (incidentalness) and engages with a news post in their feed depends not only on how they
have customized their network (personalization), what their friends post or the majority of users
are interested in (sociality), but also on the ability of the single post (granularity) to attract the
user’s attention amid a diverse blend of content (non-exclusivity).
While the PINGS framework is largely platform-independent and applicable to most
current social media sites, the five attributes are mixed differently on different platforms,
suggesting that their significance for news-related outcomes varies as well. Indeed, one should
not think of the framework components in binary terms (e.g., a news experience being social or
not), but more as a matter of degreeespecially from the users’ perspective. For example, it
might be more important for a user’s willingness to engage with a news post if two of their best
friends shared it compared to the post having 25,000 likes by unknown others. Moreover, we can
also think of different social media platforms as providing more or less personalized, incidental,
non-exclusive, granular, and social news experiences. Regardless of user behavior, Twitter
seems to be a platform that is generally more “newsful” (Ju et al., 2014) and—through its
‘trending topics’ section—one that often features the news of the day (Boukes, 2019, p. 37).
Accordingly, it might be easier for users to stumble upon current affairs information on
Twitter—even if they are not interested in it. Instagram, on the contrary, has a feed that is
organized in a way that users, apart from advertisements, only see content from accounts and
hashtags they follow while more serendipitous encounters are confined to the heavily
personalized ‘search & explore’ section. Furthermore, given the uniform visual presentation of
posts as square tiles on Instagram, it might be even harder for news posts to compete against
personal photos by friends or the aestheticized content of influencers. Considering the different
digital architectures of social media platforms is thus crucial to make sense of users’ news
experiences and the effects of social media news use. The PINGS framework allows researchers
to locate every platform on a spectrum (e.g., being high in personalization, low on sociality, etc.)
and to theorize about how the mix of the five attributes might consequently affect the outcomes
of using news.
Although the PINGS framework is largely user-centric and focused on the experiences of
individual users, it also asks us to think about the wider societal implications of using news on
social media. What does it mean for a society’s social cohesion or overall information supply
when citizens increasingly experience news in a personalized, incidental, non-exclusive,
granularized, and social fashion? There is evidence that not only is (news) content increasing in
volume, but that the span of collective attention towards specific topics has gotten narrower
(Lorenz-Spreen et al., 2019)—a dynamic that might partly result from social media information
environments in general and characteristics such as non-exclusivity and granularity in particular
(see also Kozyreva et al., 2020, p. 125). Moreover, considering the focus on journalistic news
content in this article, one might scrutinize how users’ experiences with news on social media
affect journalism in a kind of ongoing feedback loop, influencing, for example, journalists’ role
conceptions or their production and distribution routines (e.g., Vázquez-Herrero et al., 2020; Xia
et al., 2020).
The scholarly debate about the uses and effects of news in social media information
environments is lively and continuing, producing insights into how people are exposed to news,
how they engage with encountered news content, and, not least, how they are affected by news
on social media. This article benefits this debate by introducing the PINGS framework, which
systemizes news experiences in social media information environments and can be used to guide
research on the conditions, opportunities, and challenges of using news on these platforms.
Recognizing that news experiences are simultaneously personalized, incidental, non-exclusive,
granularized, and social, is crucial to understand how people navigate social media information
environments and what they are (un)able to gain from their use. Being platform-independent and
focused on high-level attributes, the PINGS framework offers a robust and fairly persistent
structure to examine social media news uses and related outcomes. Moreover, it helps to
recognize both intentional and unintentional blind spots in extant empirical research: For
example, did an experiment account for the fact that news posts are mixed with other types of
content on social media? Do survey measures of incidental news exposure take into
consideration that stumbling upon news is not a universal experience? And do content analyses
of social media news posts acknowledge how the number of likes or comments influence the
visibility of a post and, consequently, its impact on users? A greater focus on these issues could
provide insights that account for what it means to use news in the current media environment.
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Figure 1
The PINGS Framework and its Components
Note: Icons created by users “Vectors Market” and “Edwin PM” from
... Information consumers are also information producers, propagating information of variable quality on to others in their networks. 5,6 It should be no surprise, then, that patients increasingly obtain their medical information from the internet where there are few safeguards to ensure that information is accurate. 7 As clinicians, we should not stand on the sidelines as these social and structural changes to our information environment put our patients at risk. ...
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A by-product of today’s hybrid media system is that genres—once uniformly defined and enforced—are now murky and contested. We develop the concept of news-ness, defined as the extent to which audiences characterize specific content as news, to capture how audiences understand and process media messages. In this article, we (a) ground the concept of news-ness within research on media genres, journalism practices, and audience studies, (b) develop a theoretical model that identifies the factors that influence news-ness and its outcomes, and (c) situate news-ness within discussions about fake news, partisan motivated reasoning, and comparative studies of media systems.
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On social media, journalistic news products compete with entertainment-oriented and user-generated contents on two different stages of news use: First, users navigate their attention through a continuous stream of information in their newsfeed and, second, they potentially click on some of these posts to spend time with the actual full-contents. The present study conceptualizes these two types of news use behaviors in social media environments as first- and second-level selective exposure. Based on this new approach, we investigated main drivers of journalistic news exposure on both exposure levels in an online survey experiment before the German federal election in 2017 (N = 210). To achieve high ecological validity, we developed a Newsfeed Exposure Observer (NEO)-Framework to recreate realistic user settings for online experiments studying selective exposure in the digital era, where news posts are complemented by popularity cues like social endorsements or individual recommendations. Findings show that, at the first level of selective exposure, attention to journalistic news posts is particularly affected by political interest. However, the decision to click on posts in the newsfeed and to spend time with the linked contents seems more strongly driven by social factors than by individual predispositions.
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Research has prominently assumed that social media and web portals that aggregate news restrict the diversity of content that users are exposed to by tailoring news diets toward the users’ preferences. In our empirical test of this argument, we apply a random-effects within–between model to two large representative datasets of individual web browsing histories. This approach allows us to better encapsulate the effects of social media and other intermediaries on news exposure. We find strong evidence that intermediaries foster more varied online news diets. The results call into question fears about the vanishing potential for incidental news exposure in digital media environments.
This article argues for new approaches to the study of incidental exposure that better account for the role of algorithms, platforms, and processes of datafication in shaping the likelihood of news exposure online. It offers a critique of three themes prominent in the incidental exposure literature: (1) incidental exposure connotes accidental exposure to news on social media, (2) news content is ubiquitous on social media, and (3) incidental exposure can be conceptually distinguished from intentional exposure to news on social media. This article proposes a new metaphor to reframe research on incidental exposure: ‘attraction’ to news.
Social network sites such as Facebook and Twitter have become a key part of online users’ news diets. On social network sites, even individuals who are not motivated to seek out news are believed to be exposed to news posts due to the sharing activities of friends or inadvertently witnessing discussions about current events. Research on this incidental news exposure (INE) has largely focused on its potential for positive effects on information gain or political participation, while simultaneously turning a blind eye to the inequalities in news exposure and engagement. This article aims to address this issue by proposing and explicating the existence of a ‘Matthew Effect’ in social media news use. It is argued that INE research needs to consider the unequal chances to both be exposed to news on social network sites and to actually engage (i.e. read and interact) with ‘accidentally’ encountered news content.
Scholarly and pragmatic definitions of the term “engagement” vary drastically. This article attempts to capture the nuances of the term by exploring journalists’ roles on social media where “engagement” is supposed to be particularly prevalent. Using in-depth interviews, we gauge the attitudes of traditional political journalists as well as those who think of themselves as “engagement specialists” about their responsibilities in interactive spaces. In addition, we analyze what kinds of engagement are happening in these spaces, and how citizens’ expectations are being articulated, in terms of journalist-audience relationship—an organic resultant of engagement. We found that journalists are taking on new kinds of roles in social spaces—often in the name of “engagement”—but that work is not always particularly interactive with citizens; rather, content is engaged with. In contrast, citizens look to journalists to play a number of roles that range from civic guide to therapist. Thus, relationship building happens sporadically. Furthermore, engagement level is dependent on the platform and its affordances. This research offers a continuum of social media engagement conceived as relationship building that can reconcile the disparities in how we define engagement, and suggests newsrooms appreciate the nuances via a series of recommendations.
When is a tweet considered news? This study uses an experimental design to isolate two features of a headline shared on Twitter to determine the impact on audience ratings of ‘news-ness.’ We examine how people rate a Twitter post about potential government shutdown depending on: the type of story headline (breaking, exclusive, fact check, opinion), and the source of the story/tweet (Associated Press, MSNBC, Fox News). Results show that headline story type and source separately impact news-ness, with partisanship conditioning the influence of source on news-ness. Moreover, we find that ratings of news-ness mediate these effects on intent to verify tweet content, such that higher ratings of news-ness results in lower intent to verify. We argue that more attention needs to be paid to the central role that perceptions of news-ness plays in driving a range of outcomes in today’s social media environment.