Abstract
The issue of Russian interference in the 2016 U.S. Presidential election has been widely debated by scholars and journalists. However, these works have not fully analyzed the ads that have been released by Facebook and the U.S. Congress. This project uses a case study to analyze the ads posted by the Russian-affiliated Internet Research Agency, considering the quantities of ads targeted to particular geographic locations, the frequency of targeting for unique keywords, and the reach and impressions of each of the ads. Further, these results are compared to results from best practices in traditional social media campaigns as a way to better understand the goals and potential impacts of the IRA ads. In conclusion, the project, by analyzing the full set of IRA ads, sheds new light on the way false information narratives were leveraged by the Russian-linked IRA.
TopBackground
The term “fake news” became a popular talking point during the 2016 Presidential election cycle, but it has existed in academic networks as a catch-all descriptor for a variety of content, from satire such as The New Yorker’s “Borowitz Report” to Photoshopped imagery, maliciously constructed false information, propaganda, and outreach pieces. Often this term is linked to the anxiety regarding the shift in distribution of news from newspaper and television stations to the online realm, where social media sites like Facebook and Twitter are used to circulate information.
Perhaps the best example to illustrate fake news comes from Dan Faltesek (2016), who describes the phenomenon as “social media news stories that feature sensational headlines referring to untrue information. These stories are produced by actors who are not mandated to do journalism and are remunerated by online ad networks.” Indeed, this illustrates how fake news agents are not only distributed largely through social networks, but also places a focus on the monetary value of false information. While the attention of individuals is not a “zero-sum” game, there is limited bandwidth for information, which necessitates the use of tools such as sensationalistic writing to capture the attention of users. Faltesek’s work suggests that users are more likely to be captivated by news that replicates traditional news writing, which makes these malicious actors invisible to the untrained eye (Faltesek, 2016).
While researchers have discussed the fact-checking apparatuses that have emerged to combat false information narratives – a term we introduce here to differentiate these advertisements from the more traditional fake news actors and artifacts typically discussed as rhetorical devices – only now are we able to better define how fake news and narratives operate in the online realm. These narratives often function as means of reinforcing narratives about race, class, and gender that help build and maintain collective identity, particularly for those users on the right of the political spectrum (Polletta & Callahan, 2017).
Key Terms in this Chapter
Click-Through Rate: The rate at which users click an advertisement in comparison to how many times it was displayed.
Memetic Communication: Derived from Richard Dawkins’ book The Selfish Gene , memes represent units of cultural expression that spread between individuals, this form of communication traces the the how memes are spread and how they impact communication practices.
Fake News: A catch-all term for intentionally false information, widely popularized during the 2016 Presidential Campaign of Donald Trump.
Epistemology: A branch of philosophy dealing with questions about knowledge and truth.
False Information Narrative: Meant to denote contexts beyond that of news, this term covers a variety of media in which false information is intentionally used to support a particular narrative.
Sociotechnical Ensembles: A theoretical approach to knowledge creation and identity that blurs the line between social agents and the larger technical systems in which they exist.