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Influence of fake news in Twitter during the 2016 US presidential election.

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 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.

SUBMITTER: Bovet A

PROVIDER: S-EPMC6315042 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Influence of fake news in Twitter during the 2016 US presidential election.

Bovet Alexandre A Makse Hernán A HA

Nature communications 20190102 1

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 flo ...[more]

PMID: 30602729

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Project description:Background Anger and extreme stress can trigger potentially fatal cardiovascular events in susceptible people. Political elections, such as the 2016 US presidential election, are significant stressors. Whether they can trigger cardiac arrhythmias is unknown. Methods and Results In this retrospective case-crossover study, we linked cardiac device data, electronic health records, and historic voter registration records from 2436 patients with implanted cardiac devices. The incidence of arrhythmias during the election was compared with a control period with Poisson regression. We also tested for effect modification by demographics, comorbidities, political affiliation, and whether an individual's political affiliation was concordant with county-level election results. Overall, 2592 arrhythmic events occurred in 655 patients during the hazard period compared with 1533 events in 472 patients during the control period. There was a significant increase in the incidence of composite outcomes for any arrhythmia (incidence rate ratio [IRR], 1.77 [95% CI, 1.42-2.21]), supraventricular arrhythmia (IRR, 1.82 [95% CI, 1.36-2.43]), and ventricular arrhythmia (IRR, 1.60 [95% CI, 1.22-2.10]) during the election relative to the control period. There was also an increase in specific types of arrhythmia, including atrial fibrillation (IRR, 1.50 [95% CI, 1.06-2.11]), supraventricular tachycardia (IRR, 3.7 [95% CI, 2.2-6.2]), nonsustained ventricular tachycardia (IRR, 1.7 [95% CI, 1.3-2.2]), and daily atrial fibrillation burden (P<0.001). No significant interaction was found for sex, race/ethnicity, device type, age ≥65 years, hypertension, coronary artery disease, heart failure, political affiliation, or concordance between individual political affiliation and county-level election results. Conclusions There was a significant increase in cardiac arrhythmias during the 2016 US presidential election. These findings suggest that exposure to stressful sociopolitical events may trigger arrhythmogenesis in susceptible people.

Dataset Information

Influence of fake news in Twitter during the 2016 US presidential election.

Publications

Influence of fake news in Twitter during the 2016 US presidential election.

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