Online disinformation in the 2020 U.S. Election: swing vs. safe states
arXiv:2402.18664 · doi:10.1140/epjds/s13688-024-00461-6
Abstract
For U.S. presidential elections, most states use the so-called winner-take-all system, in which the state's presidential electors are awarded to the winning political party in the state after a popular vote phase, regardless of the actual margin of victory. Therefore, election campaigns are especially intense in states where there is no clear direction on which party will be the winning party. These states are often referred to as swing states. To measure the impact of such an election law on the campaigns, we analyze the Twitter activity surrounding the 2020 US preelection debate, with a particular focus on the spread of disinformation. We find that about 88% of the online traffic was associated with swing states. In addition, the sharing of links to unreliable news sources is significantly more prevalent in tweets associated with swing states: in this case, untrustworthy tweets are predominantly generated by automated accounts. Furthermore, we observe that the debate is mostly led by two main communities, one with a predominantly Republican affiliation and the other with accounts of different political orientations. Most of the disinformation comes from the former.
arXiv commentarXiv admin note: text overlap with arXiv:2303.12474
References in corpus (16)
- Fast unfolding of communities in large networks
- The science of fake news
- Near linear time algorithm to detect community structures in large-scale networks
- The Rise of Social Bots
- The spread of low-credibility content by social bots
- Influence of fake news in Twitter during the 2016 US presidential election
- The statistical mechanics of networks
- The Statistical Physics of Real-World Networks
- Anatomy of an online misinformation network
- Analytical maximum-likelihood method to detect patterns in real networks
- Maximum likelihood: extracting unbiased information from complex networks
- Randomizing bipartite networks: the case of the World Trade Web
- Inferring monopartite projections of bipartite networks: an entropy-based approach
- The role of bot squads in the political propaganda on Twitter
- Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections
- Networked partisanship and framing: a socio-semantic network analysis of the Italian debate on migration