Computational propaganda distributes large amounts of misinformation about politics and public policy over social media platforms. The combination of automation and propaganda can significantly impact public opinion during important policy debates, elections, and political crises. We collected data on automation and junk news using major hashtags related to politics in the state of Michigan in the lead up to the 2016 US Presidential Election. (1) In Michigan, conversation about politics over Twitter mirrored the national trends in that Trump-related hashtags were used more than twice as often as Clinton-related hashtags. (2) Social media users in Michigan shared a lot of political content, but the amount of professionally researched political news and information was consistently smaller than the amount of extremist, sensationalist, conspiratorial, masked commentary, fake news and other forms of junk news. (3) Not only did such junk news “outperform” real news, but the proportion of professional news content being shared hit its lowest point the day before the election.

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Philip N. Howard, Gillian Bolsover, Bence Kollanyi, Samantha Bradshaw, Lisa-Maria Neudert.  “Junk News and Bots during the U.S. Election: What Were Michigan Voters Sharing Over Twitter?” Data Memo 2017.1. Oxford, UK: Project on Computational Propaganda.