How did an election fraud narrative spread online? Testing theories us-ing machine learning and natural language processing

Authors

DOI:

https://doi.org/10.32473/flairs.37.1.135380

Keywords:

artificial intelligence, natural language processing, election security, election fraud, social identity theory, network analysis, Named Entity Recognition, duplicate detection, dominion voting

Abstract

In this study, we investigated 1) how election fraud narratives propagated on social media, and 2) the role of influential actors in the process of building and spreading the election fraud narratives. We applied machine learning (ML) and natural language processing (NLP) methods to examine Twitter data related to an election fraud narrative following the 2020 Presidential election. We identified influential actors and found evidence for the former President’s use of social media to cue group identity. 

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Published

13-05-2024

How to Cite

Hagen, L., Ford, D., Edwards, J., Dinh, L., DePaula, N., & Scacco, J. (2024). How did an election fraud narrative spread online? Testing theories us-ing machine learning and natural language processing . The International FLAIRS Conference Proceedings, 37(1). https://doi.org/10.32473/flairs.37.1.135380