The Spread of Top Misinformation Articles on Twitter in 2017: Social Bot Influence and Misinformation Trends

Abstract

Misinformation and how it spreads on Twitter is important for understanding the automated realm our world has developed into over time. Scholarship has focused on manipulation of information, but less research has focused on misinformation on Twitter. This thesis analyzed how social bots influenced the spread of top misinformation articles compared to non-bot users on Twitter in 2017. The study analyzed top misinformation and fact-checking article topic trends from January 1, 2017 to December 31, 2017, in the weeks leading up to and during the first year of Donald J. Trump’s presidency in the U.S. The top articles refer to those that spread the farthest on Twitter in 2017. The case study utilized descriptive statistics to analyze trends in the data and a qualitative content analysis to establish topics and subtopics of misinformation articles (N = 480). For misinformation article topics, referring to the most popular topics spread by users in 2017, “general politics” and “Trump” were the most common topic and sub-topic. For fact-checked articles, the most common article topic and subtopic were also “general politics” and “Trump.” The most common misinformation sources were online “news” outlets Breitbart and Infowars. While this doesn’t suggest that these are “fake news” websites, the findings show that these “news” outlets regularly post misleading information. Misinformation articles also spread more rapidly on Twitter than fact-checked articles did. This suggests that users spread misinformation more commonly, rather than fact-checked articles. Lastly, the “most active users” of misinformation articles on Twitter were examined to discover social bot trends. The findings show that social bots impacted the spread of misinformation articles, mostly related to topics about “Trump” and “general politics.”