Influence of fake news in Twitter during the 2016 US presidential election Alexandre Bovet1;2;3, Hern´anA. Makse1;∗ 1) Levich Institute and Physics Department, City College of New York, New York, New York 10031, USA 2) ICTEAM, Universit´eCatholique de Louvain, Avenue George Lema^ıtre 4, 1348 Louvain-la-Neuve, Belgium 3) naXys and Department of Mathematics, Universit´ede Namur, Rempart de la Vierge 8, 5000 Namur, Belgium. *
[email protected] Abstract The dynamics and influence of fake news on Twitter during the 2016 US presidential election remains to be clarified. Here, we use a dataset of 171 million tweets in the five months preceding the election day to identify 30 million tweets, from 2.2 million users, which contain a link to news outlets. Based on a classification of news outlets curated by www.opensources.co, we find that 25% of these tweets spread either fake or extremely biased news. We characterize the networks of these users to find the most influential spreaders of fake and traditional news and use causal modelling to uncover how fake news influenced the presidential election. We find that, while top influencers spreading traditional center and left leaning news largely influence the activity of Clinton supporters, this causality is reversed for the fake news: the activity of Trump supporters influences the dynamics of the top fake news spreaders. 1 Introduction Recent social and political events, such as the 2016 US presidential election [1], have been marked by a growing number of so-called \fake news", i.e. fabricated information that disseminate deceptive content, or grossly distort actual news reports, shared on social media platforms.