ORIGINAL RESEARCH article

Front. Polit. Sci.

Sec. Elections and Representation

Volume 7 - 2025 | doi: 10.3389/fpos.2025.1488363

Detecting and Measuring Social Media Attacks on American Election Officials

Provisionally accepted
  • 1Princeton University, Princeton, New Jersey, United States
  • 2Harvard University, Cambridge, Massachusetts, United States
  • 3Stanford University, Stanford, California, United States
  • 4California Institute of Technology, Pasadena, United States

The final, formatted version of the article will be published soon.

The 2020 presidential election saw election officials experience physical and social media threats, harassment, and animosity. Although little research exists regarding animosity toward US election officials, observers noted a sharp increase in 2020 in animosity toward US election officials. The harassment of election officials hindered their work in administering a free and fair election and may have generated doubts about electoral integrity. Our study:• Proposes a unique measurement and modeling strategy applicable across many social media networks to study toxicity directed at officials, institutions, or groups;• Collects a novel dataset of social media conversations about election administration in the 2020 election;• Uses joint sentiment-topic modeling to identify toxicity from the reactions of the public and election officials, and uses dynamic vector autoregression models to determine the temporal structure of the toxic conversations directed at election officials.• Finds that the level of animosity towards election officials spikes immediately after the election; that hostile topics overall make up about a quarter of the discussion share during this period, increasing to about 60% following the election; and that hostile topics come from left-and right-wing partisans.Our article concludes by discussing how similar data collection and topic modeling approaches could be deployed in future elections to monitor trolling and harassment of election officials, and to mitigate similar threats to successful election administration globally.

Keywords: election officials, Topic Modeling, Social Media, Election administration, sentiment analysis

Received: 29 Aug 2024; Accepted: 15 Apr 2025.

Copyright: © 2025 Dey, Ebanks, Hashash and Alvarez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Daniel Ebanks, Harvard University, Cambridge, MA 02138, Massachusetts, United States

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