Influence of fake news in Twitter during the 2016 US presidential election
arXiv:1803.08491 · doi:10.1038/s41467-018-07761-2
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.
arXiv commentUpdated to latest revised version
References in corpus (9)
- The Rise of Social Bots
- Influence maximization in complex networks through optimal percolation
- The spread of low-credibility content by social bots
- Velocity and hierarchical spread of epidemic outbreaks in scale-free networks
- Science vs Conspiracy: collective narratives in the age of (mis)information
- Hoaxy: A Platform for Tracking Online Misinformation
- Users Polarization on Facebook and Youtube
- Validation of Twitter opinion trends with national polling aggregates: Hillary Clinton vs Donald Trump
- Trend of Narratives in the Age of Misinformation
Cited by in corpus (64)
- The COVID-19 Social Media Infodemic
- Botometer 101: Social bot practicum for computational social scientists
- Social Media Polarization and Echo Chambers in the Context of COVID-19: Case Study
- Shifting Polarization and Twitter News Influencers between two U.S. Presidential Elections
- The role of bot squads in the political propaganda on Twitter
- Investigating Italian disinformation spreading on Twitter in the context of 2019 European elections
- It's All in the Embedding! Fake News Detection Using Document Embeddings
- Topology comparison of Twitter diffusion networks effectively reveals misleading information
- Exposure to Social Engagement Metrics Increases Vulnerability to Misinformation
- MisRoBÆRTa: Transformers versus Misinformation
- One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study
- Right and left, partisanship predicts (asymmetric) vulnerability to misinformation
- The Limited Reach of Fake News on Twitter during 2019 European Elections
- Neutral bots probe political bias on social media
- Modeling the spread of fake news on Twitter
- The Perils & Promises of Fact-checking with Large Language Models
- Flow of online misinformation during the peak of the COVID-19 pandemic in Italy
- SEMI-FND: Stacked Ensemble Based Multimodal Inference For Faster Fake News Detection
- Information disorders on Italian Facebook during COVID-19 infodemic
- Unveiling Coordinated Groups Behind White Helmets Disinformation
- The optical properties of few-layer InSe
- Conspiracy vs science: A large-scale analysis of online discussion cascades
- Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo
- The Systemic Impact of Deplatforming on Social Media
- Analysing Twitter Semantic Networks: the case of 2018 Italian Elections
- Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections
- Characterizing networks of propaganda on Twitter: a case study
- Temporal Dynamics of Coordinated Online Behavior: Stability, Archetypes, and Influence
- Spreading dynamics of information on online social networks
- How does Twitter account moderation work? Dynamics of account creation and suspension on Twitter during major geopolitical events
- Homophily on social networks changes evolutionary advantage in competitive information diffusion
- Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data
- Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter
- Containing misinformation spreading in temporal social networks
- Beyond network centrality: Individual-level behavioral traits for predicting information superspreaders in social media
- Network diffusion capacity unveiled by dynamical paths
- Sustainable Development Goals as unifying narratives in large UK firms' Twitter discussions
- Misinformation spreading on correlated multiplex networks
- Characterizing Engagement Dynamics across Topics on Facebook
- Fake news and rumors: a trigger for proliferation or fading away
- Forecasting countries' gross domestic product from patent data
- Postmortem memory of public figures in news and social media
- Modeling the amplification of epidemic spread by individuals exposed to misinformation on social media
- On node ranking in graphs
- Selecting Energy Efficient Inputs using Graph Structure
- Modelling election dynamics and the impact of disinformation
- Unifying information propagation models on networks and influence maximization
- XAI in Automated Fact-Checking? The Benefits Are Modest and There's No One-Explanation-Fits-All
- Differential impact from individual versus collective misinformation tagging on the diversity of Twitter (X) information engagement and mobility
- Online disinformation in the 2020 U.S. Election: swing vs. safe states
- The influence of coordinated behavior on toxicity
- Centralities in complex networks
- Mobile Phone Data for Children on the Move: Challenges and Opportunities
- Predicting Nodal Influence via Local Iterative Metrics
- Disentangling sources of influence in online social networks
- Bots against Bias: Critical Next Steps for Human-Robot Interaction
- The Effect of Social Media on Shaping Individuals Opinion Formation
- FNDaaS: Content-agnostic Detection of Fake News sites
- Design and analysis of tweet-based election models for the 2021 Mexican legislative election
- Can You Fool AI by Doing a 180? $\unicode{x2013}$ A Case Study on Authorship Analysis of Texts by Arata Osada
- Linking the Dynamics of User Stance to the Structure of Online Discussions
- Social Diffusion Sources Can Escape Detection
- Optimal control of a kinetic model describing social interactions on a graph
- Italian Twitter semantic network during the Covid-19 epidemic