Frontiers in Big Data (Jul 2021)
Marginalizing the Mainstream: How Social Media Privilege Political Information
Abstract
The following reports on research undertaken concerning the “misinformation problem” on social media during the run-up to the U.S. presidential elections in 2020. Employing techniques borrowed from data journalism, it develops a form of cross-platform analysis that is attuned to both commensurability as well as platform specificity. It analyses the most engaged-with or top-ranked political content on seven online platforms: TikTok, 4chan, Reddit, Twitter, Facebook, Instagram and Google Web Search. Discussing the extent to which social media platforms marginalize mainstream media and mainstream the fringe, the analyses found that TikTok parodies mainstream media, 4chan and Reddit dismiss it and direct users to alternative influencer networks and extreme YouTube content. Twitter prefers the hyperpartisan over it. Facebook’s “fake news” problem also concerns declining amounts of mainstream media referenced. Instagram has influencers (rather than, say, experts) dominating user engagement. By comparison, Google Web Search buoys the liberal mainstream (and sinks conservative sites), but generally gives special interest sources, as they were termed in the study, the privilege to provide information rather than official sources. The piece concludes with a discussion of source and “platform criticism”, concerning how online platforms are seeking to filter the content that is posted or found there through increasing editorial intervention. These “editorial epistemologies”, applied especially around COVID-19 keywords, are part of an expansion of so-called content moderation to what I call “serious queries”, or keywords that return official information. Other epistemological strategies for editorially moderating the misinformation problem are also treated.
Keywords
