The small, disloyal fake news audience: The role of audience availability in fake news consumption

Abstract

In light of the recent US election, many fear that “fake news” has become a force of enormous reach and influence within the news media environment. We draw on well-established theories of audience behavior to argue that the online fake news audience, like most niche content, would be a small subset of the total news audience, especially those with high availability. By examining online visitation data across mobile and desktop platforms in the months leading up to and following the 2016 presidential election, we indeed find the fake news audience comprises a small, disloyal group of heavy Internet users. We also find that social network sites play an outsized role in generating traffic to fake news. With this revised understanding, we revisit the democratic implications of the fake news crisis.

The facts of fake news: A research review

“…Despite fake news hogging the spotlight of media coverage and criticism (Tandoc, Jenkins, et al, 2018), as well as initial analyses that demonstrated the rise in audience engagement with fake news (Silverman, ), a few studies argued that the size of the audience exposed to fake news is rather small, at least in the United States. An examination of audience online usage data in the months around the 2016 presidential elections in the United States found that “the fake news audience is small and comprises a subset of the Internet's heaviest users, while the real news audience commands a majority of the total Internet audience” (Nelson & Taneja, , p. 3732). Similarly, an analysis of Twitter users in the United States found that of all the accounts examined, only about 0.1% were responsible for almost 80% of shares of content from fake news sources (Grinberg, Joseph, Friedland, Swire‐Thompson, & Lazer, ).…”

“…Specifically, scholarly research has defined fake news as a form of falsehood intended to primarily deceive people by mimicking the look and feel of real news (Tandoc et al, ). While initial research has shown that only a small fraction of the online audience is exposed to fake news, for this small group of people, the impact of fake news can be quite substantial (Grinberg et al, ; Nelson & Taneja, ) and can also lead to what can be termed as second‐hand disinformation. Studies have identified cognitive processes that make individuals more prone to the influence of fake news, such as confirmation bias, selective exposure, and lack of analytical thinking (Lazer et al, ; Pennycook & Rand, ; Spohr, ).…”

The reach of commercially motivated junk news on Facebook

“…Quantitative research has mostly overlooked the phenomenon of money-driven junk news, focussing on junk news and fake news characterized by political content and ideological motivation. Whereas the audience for political fake news is relatively small, consisting of politically polarized, heavy media users [11,22], commercial junk news appears to reach the broad audience it aims for. We have shown that commercial junk news receives significantly more user interactions (reactions, comments and shares) than mainstream news on Facebook.…”

“…Combining survey responses with web tracking data, Guess et al [11] estimate that in the weeks before and after the 2016 US presidential election 1 in 4 Americans visited a fake news site, but that most fake news was consumed by a small group of conservatives. Studying the fake news audience in the US, Nelson and Taneja [22] similarly conclude that this is a small subset of the heaviest Internet users. Political fake news is, essentially, niche content (ibid.).…”

9. Rethinking Democracy with Social Media

“…23 Likewise, another study examined online visitation data across mobile and desktop platforms in the months leading up to and following the 2016 presidential election and found that the fake news audience comprises a small, disloyal group of heavy internet users. 24 For computational propaganda, there is little doubt of the scale, and it is being extensively gathered and analysed by the Computational Propaganda project at the University of Oxford. 25 An analysis of 9 million tweets from the 2016 presidential campaign found that one-third of pro-Trump Twitter traffic was driven by accounts that were bots or highly automated, compared with one-fifth of pro-Clinton traffic, and such an analysis has been performed for several elections since then.…”