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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 information flow to find the most influential spreaders of fake and traditional news and use causal modeling 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.
It is a widely accepted fact that state-sponsored Twitter accounts operated during the 2016 US presidential election spreading millions of tweets with misinformation and inflammatory political content. Whether these social media campaigns of the so-c
It is a widely accepted fact that state-sponsored Twitter accounts operated during the 2016 US presidential election, spreading millions of tweets with misinformation and inflammatory political content. Whether these social media campaigns of the so-
The advent of social media changed the way we consume content favoring a disintermediated access and production. This scenario has been matter of critical discussion about its impact on society. Magnified in the case of Arab Spring or heavily critici
Identifying and characterizing disinformation in political discourse on social media is critical to ensure the integrity of elections and democratic processes around the world. Persistent manipulation of social media has resulted in increased concern
Today, an estimated 75% of the British public access information about politics and public life online, and 40% do so via social media. With this context in mind, we investigate information sharing patterns over social media in the lead-up to the 201