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What to Believe? Social Media Commentary and Belief in Misinformation

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Abstract

Americans are increasingly turning to social media for political information. However, given that the average social media user only clicks through on a small fraction of the political content available, the brief article previews that appear in the News Feed likely serve as shortcuts to political information. Yet, in addition to sharing political news, social media also allow users to make their own comments on news posts, comments which may challenge or distort the information contained in the articles. In this paper, we first analyze how social media posts on Twitter and Facebook differ from the actual content of their linked news articles, finding that social media comments regularly misrepresent the facts reported in the news. We then use a survey experiment to test the consequences of these information discrepancies. Specifically, we randomly assign individuals to read a full news article, a news article preview post (as seen on Facebook), or a news article preview with misinformative social commentary attached. We find that individuals in the social commentary conditions are more misinformed about the featured topic, tending to report the factually-incorrect information relayed in the comments rather than the factually-correct information embedded within the article preview.

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Notes

  1. Trump’s tweet was made on March 11, 2018. The most recent Rasmussen poll before that date was released on March 9, 2018, and showed Trump’s approval rating to be 44%.

  2. http://harvardharrispoll.com/wp-content/uploads/2017/05/HCAPS_HarrisPoll_May-Wave_Top-Line-Memo_Registered-Voters.pdf.

  3. Crimson Hexagon (https://www.crimsonhexagon.com/) is a data vendor allowing subscribers to access data from Twitter, Facebook, Instagram, Blogs, Forums, News, Comments, Reviews, YouTube, and other sources. Crimson Hexagon provides access to over 1 trillion social media posts going back to 2008. The platform provides sentiment scores using its proprietary algorithms and allows users to extract random samples of the posts.

  4. The full text of the articles is available in the Online Appendix.

  5. https://twitter.com/realdonaldtrump/status/886588838902206464.

  6. In the full article condition, this was phrased as the person who “wrote” the article.

  7. Choices included 15%, 23%, 36%, 49%, and a “Don’t know” option. The Yahoo! News article and its preview reported that Trump’s approval rating was 36% at the time, while the liberal and conservative commentaries suggested that his approval rating was actually 23 or 49%, respectively.

  8. Choices included “Sampled more Democrats,” “Sample more Republicans,” “Inaccurate during the 2016 election,” “Funded by liberals,” and a “Don’t know” option. The Yahoo! News article reported Trump’s claims that the poll was inaccurate during the 2016 election, while the liberal and conservative commentaries suggested that the poll sampled more Republicans or Democrats, respectively. The article preview did not include any information about survey flaws.

  9. Because H4 is concerned only in the relationship whether partisan motivated reasoning explains belief in misinformation, H4’s analysis is limited to only those assigned to the misinformative experimental conditions.

  10. Petty and Cacioppo’s (1981, 1986) Elaboration Likelihood Model considers two routes to persuasion: a central route in which individuals thoughtfully examine new pieces of information, and a peripheral route in which persuasion occurs as the result of some heuristic (e.g., a source cue) rather than careful consideration. Because individuals motivated by a need for cognition may be more likely to scrutinize competing pieces of information than those motivated by a need for affect (see Arceneaux and Vander Wielen 2017), we include measures for both NFC (Cacioppo et al. 1984) and for NFA (Maio and Esses 2001) as control variables in our analyses. We also include measures of political knowledge (measured using five factual questions about politics), age, gender, race, education, income, and party (with higher values indicating identification with the Republican party). The full survey and balance tests can be found in the Online Appendix.

  11. http://news.gallup.com/poll/195542/americans-trust-mass-media-sinks-new-low.aspx.

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Authors and Affiliations

  1. York College of Pennsylvania, York, PA, USA

    Nicolas M. Anspach

  2. University of California, San Diego, San Diego, CA, USA

    Taylor N. Carlson

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  1. Nicolas M. Anspach
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  2. Taylor N. Carlson
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Correspondence to Nicolas M. Anspach.

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Anspach, N.M., Carlson, T.N. What to Believe? Social Media Commentary and Belief in Misinformation. Polit Behav 42, 697–718 (2020). https://doi.org/10.1007/s11109-018-9515-z

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