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Journal of Computer-Mediated Communication
Social Media as Information Source: Recency
of Updates and Credibility of Information
∗
David Westerman
Department of Communication, North Dakota State University, Department #2310, PO Box 6050, Fargo, ND
58108
Patric R. Spence
Division of Instructional Communication & Research, College of Communication and Information, University of
Kentucky, 310 Lucille Little Library (LCLI), Lexington, KY 40506-0224
Brandon Van Der Heide
School of Communication, The Ohio State University, 3016 Derby Hall, 154, North Oval Mall Columbus, OH
43210-1339
Social media are increasingly being used as an information source, including information related
to risks and crises. The current study examines how pieces of information available in social media
impact perceptions of source credibility. Specifically, participants in the study were asked to view 1 of
3 mock Twitter.com pages that varied the recency with which tweets were posted and then to report
on their perceived source credibility of the page owner. Data indicate that recency of tweets impacts
source credibility; however, this relationship is mediated by cognitive elaboration. These data suggest
many implications for theory and application, both in computer-mediated communication and crisis
communication. These implications are discussed, along with limitations of the current study and
directions for future research.
Key words: System-Generated Cues, Social Media, Recency, Twitter.
doi:10.1111/jcc4.12041
Newer communication technologies have increased the possibilities for how people can send and receive
information. Social mediaare one such technology that has seen increased usage as an information source
(Pepitone, 2010). For example, social media are being used to seek information about serious topics,
such as circulating up-to-the minute information about cholera outbreaks in Haiti and identifying clean
water sources during this outbreak (Sutter, 2010). Social media has also seen a great deal of usage by
those seeking health information, with 59% of adult Americans (80% of internet users) reporting that
they have accessed this type of information online (Fox, 2011). As this Pew Report suggests ‘‘people use
online social tools to gather information, share stories, and discuss concerns’’ (Fox, 2011, p. 5). Similarly
health professions and organizations are seeing the advantages of adopting social media because it is seen
as an information equalizer allowing access to health care information to populations who, in the past,
would not have this access (McNab, 2009). It provides a sense of privacy for the information seeker in
that he/she does not have to disclose personal information in order to obtain health related information.
∗
Accepted by previous editor Maria Bakardjieva
Journal of Computer-Mediated Communication 19 (2014) 171–183 © 2013 International Communication Association 171
However, a major question surrounding the use of social media as an information source is how
people assess the source credibility of this information (Westerman, Spence & Van Der Heide, 2012).
This question becomes especially important to answer for users of social media, as the gatekeeping
function switches from producers to consumers of information for newer technologies (Haas &
Wearden, 2003). These newer channels provide new pieces of information not available in ‘‘legacy’’
channels which may be used to make credibility judgments, such as the ability to see how quickly and
recently a page host updates their page. The current study examines how this piece of information
impacts a viewer’s cognitive elaboration and their perceived credibility of the source.
Social Media and Credibility Judgments
The types of information suggested in the first paragraph of this paper share at least one thing
in common: they all deal with uncertain situations highlighted by potential danger. Overall, when
uncertainty represents potential danger, people actively engage in information seeking (Brashers,
Neidig, Haas, Dobbs, Cardillo, & Russell, 2000; Spence, Lachlan & Griffin, 2007). They will seek
information from a variety of sources, and will constantly update their information. Mass media have
historically been a dominant source (Murch, 1971), possibly because they are generally thought to
provide credible, valuable, and timely information (Heath, Liao, & Douglas, 1995). However, along
with traditional forms of media, newer media are increasingly available for information seeking. One
channel that provides many opportunities for this purpose is the Internet. Research suggests that people
use the Internet in seeking information about crises (Spence, Westerman, Skalski, Seeger, Sellnow, &
Ulmer, 2006). More recently, social media have provided a new and potentially powerful platform for
people to use in seeking such information.
Social media are a general category of channels and applications that highlight collaboration and
working together to create and distribute content. This collaboration not only consists of creating
content together, but also discussing the content in an attempt to improve it collaboratively and to
come to a shared understanding of it. Thus, social media are built upon a fundamental characteristic of
Web 2.0: they are sites for harnessing collective intelligence (O’Reilly & Battelle, 2009). Many examples
of social media exist (e. g., Digg, Facebook, Youtube, Flickr), but one that holds great promise as a
social medium for information is Twitter (http://www.twitter.com). Twitter is a micro-blogging service
that began in March of 2006 (twitter.com).
The presence of risk raises an important issue for the consumption of social media. Often the
front lines of information come from eyewitnesses who are reporting on very recent events. In many
cases, even traditional mass media sources such as major news outlets glean information from these
sources prior to breaking news and providing information. Technological challenges in areas afflicted
by crises (i.e., down satellite connections, etc.) may slow official news correspondent reports, but
social media reports may be much more swiftly distributed. For example, during the January 2010
Haitian earthquake, social media played a key role in disseminating information about this tragedy
(Bunz, 2010). As Sutton, Palen, and Shklovski (2008) suggest, social media are gaining prominence as
an information source in disaster and risk time even though the accuracy of the information shared
through these channel is often unclear. This makes it imperative to learn more about how people
evaluate the information they consume on social media websites, especially judgments of the credibility
of this information.
Perceived source credibility has been defined as ‘‘judgments made by a perceiver ...concerning the
believability of a communicator’’ (O’Keefe, 1990, p. 181). Although there is debate about the precise
factor-structure of source credibility (see Cronkhite & Liska, 1976), one factor structure commonly
found includes three dimensions of source credibility: expertise/competence (i. e., the degree to which
172 Journal of Computer-Mediated Communication 19 (2014) 171– 183 © 2013 International Communication Association
a perceiver believes a sender to know the truth), trustworthiness (i. e., the degree to which a perceiver
believes a sender will tell the truth as he or she knows it), and goodwill (i. e., the degree to which a
perceiver believes a sender has his or her best interests at heart.)
Perceived source credibility becomes an increasingly important variable to examine within social
media, especially in terms of crisis and risk information. This is because with the increasing amount
of information available through newer channels, the gatekeeping function seems to shift away from
producers of content and onto consumers of that content (Haas & Wearden, 2003). First conceptualized
and coined by Lewin (1947), and applied to the study of news by White (1950), gatekeeping is the
process through which content creators decide what stories will be covered and reported, and thus,
what information is released to consumers. Traditionally there are many people who act as gatekeepers,
including journalists, editors, and possibly even advertisers and owners (Shoemaker & Vos, 2009).
Along the way, these gatekeepers are assumed to be checking information for veracity, and can be an
important part in the process of ensuring the credibility of that information (Salcito, 2009), and are
likely perceived to be doing so by the public (Reese & Ballinger, 2001).
The continued growth of new media has meant that information consumers are now far less
beholden to what passes through traditional gatekeepers and are able to bypass gatekeepers altogether
and turn directly to primary information sources, many of which are information consumers themselves.
Because information provided in newer channels often lacks professional gatekeepers to check content,
and thus, lacks some of the traditional markers used to determine source credibility, consumers become
more responsible for making decisions about the credibility of information online. Therefore in new
media environments the gates are now located not only with the information providers but also with the
information consumers, who in the new media environment are acting as their own gatekeepers (Kovach
& Rosenstiel, 1999). This change has created a shift from the traditional notion of ‘‘gatekeeping’’ to
what Bruns (2008) has referred to as ‘‘gatewatching.’’ Gatewatchers are unable to control the gates
through which information passes, but instead keep a constant eye at the gates, and pass what flows
through those gates onto others who then make the choice about the topic relevance and usefulness.
Therefore gatewatchers fundamentally promote or diffuse information by making sources or stories
known to others in the new media environment. Rather than publishing unique information, they make
others’ information known and add to it. This can be seen in environments such as Facebook when a
user publishes a link and then comments on it, and similarly in Twitter.com where one does the same
thing or where the user reposts a link. In many respects, this is a hallmark of social media in general;
cocreation of content. This notion of ‘‘gatewatching’’ is echoed by Sundar (2008), who stated ‘‘The
digital media universe thus presents a dual challenge: (1) the overload of information, entertainment,
and other offerings that constantly need organizing and (2) the lack of assurance of any uniformity in
content quality, which necessitates a continual monitoring of credibility on the part of users’’ (p. 77).
It is important to consider that credibility is a perception, and thus is not a quality inherent within
a channel or source itself (Fogg & Tseng, 1999). Therefore, many things can impact the perceived
credibility of online materials (Metzger, Flanagan, Eyel, Lemus, & McCann, 2003). One model created
to articulate and explain the process of making credibility judgments in online settings, and thus a
useful framework for explaining ways in which consumers may enact their own personal process of
gatekeeping with this type of information, is the MAIN model (Sundar, 2008).
The MAIN Model and Recency of Updates
The MAIN model (Sundar, 2008) describes technological affordances that allow people to heuristically
process cues when making judgments about the credibility of an online source. According to the model,
system-generated pieces of information known as metrics are one type of affordance which can be used
Journal of Computer-Mediated Communication 19 (2014) 171–183 © 2013 International Communication Association 173
as a heuristic in making credibility judgments. One metric that may be especially heuristically appealing
to people is an agency cue. Agency cues capitalize on heuristics that emphasize credibility cues that, for
example, are computer- (rather than user-) generated.
One heuristic Sundar (2008) argues is often utilized is known as the machine heuristic,whichisa
shortcut through which people assign greater credibility to information that is verified or chosen by a
machine or computer than by a person. People likely use this shortcut because a machine is seen as
something that has no thoughts, emotions, or other biases, and therefore is perceived to be free from
bias (whether or not the algorithm is actually free from bias.) This lack of perceived bias from a machine
leads to a greater trust in the information provided by machines compared to the information provided
by people such as editors, producers, and the like (Sundar & Nass, 2001). Similarly, this heuristic
may also impact the way that consumers of online information process system-generated cues. These
cues can even influence credibility judgments more strongly than the content of the message itself,
depending on the degree to which such a heuristic is activated and how heuristically or peripherally a
message is processed by a user. Past research exploring impression formation on Facebook has found
that system-generated cues can be important determinants of social judgments about social media users
(Kleck, Reese, Behnken, & Sundar, 2007; Tong, Van Der Heide, Langwell, & Walther, 2008; Utz, 2010),
suggesting that system-generated cues can affect interpersonal judgments of a profile owner.
One system-generated cue that could be important for credibility judgments is the recency (or
immediacy) of postings in this type of social media. As Sundar (2008) suggests, ‘‘[m]ore complex
examples of autogenerated cues appear in the form of navigational aids offered by algorithms used
in search-engine and aggregator sites such as Google News, which transmits cues about the relative
recency of the information, among other attributes. These appear as part of—or surrounding—the
central content of the site, and emit ‘‘information scent’’ helpful in making quick decisions about the
quality of the information available for consumption” (p. 78).
Social media seem designed to cater to those who want information in real time. As Levinson (2009)
has pointed out, one of Twitter’s hallmarks is the immediacy of messages. One important avenue to
study is how this immediacy, or recency of updates, acts as a cue that can impact credibility. Fogg
et al. (2001) found that something they call the ‘‘amateurism’’ of a website has the biggest impact of
decreasing credibility. One of the biggest markers of ‘‘amateurism’’ as they present it is the speed (or
recency) of updates. In fact, as they put together their amateurism scale, the two items with the biggest
impact on credibility deal with recency of updates, such that updating more frequently is associated with
higher credibility. As credibility is a perception, and not something inherent in the channel or website
itself, there is no reason to believe that the recency of updating should not also apply to the source of the
information presented on a social media site. Furthermore, if, as the machine heuristic (Sundar, 2008)
suggests, information provided by a machine (or a system-generated cue) offers especially valuable
credibility information because of people’s general operating heuristic that ‘‘machines don’t lie,’’ and
when this heuristic is paired with the recency principle highlighted by Fogg et al. (2001), a strong
influence on credibility judgments may exist. This leads to the first hypothesis of the current study:
H1: Recency of updating on a social media site will be positively associated with source credibility
of the site’s source.
Another important concept to examine for social media and credibility is cognitive elaboration.
Cognitive elaboration is demonstrated in active participation in information processing (Defleur &
Ball-Rokeach, 1989). This involvement process manifests in the mental process of attention, recognition
and subsequent elaboration (Greenwald & Leavitt, 1984). A central tenet of involvement is the sense
174 Journal of Computer-Mediated Communication 19 (2014) 171– 183 © 2013 International Communication Association
Social Media and Credibility Judgments