ElectionRumors2022: A Dataset of Election Rumors on Twitter During the 2022 US Midterms

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Schafer, Joseph S, Duskin, Kayla, Prochaska, Stephen, Wack, Morgan, Beers, Anna, Bozarth, Lia, Agajanian, Taylor, Caulfield, Mike, Spiro, Emma S, Starbird, Kate
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917730848866304
author Schafer, Joseph S
Duskin, Kayla
Prochaska, Stephen
Wack, Morgan
Beers, Anna
Bozarth, Lia
Agajanian, Taylor
Caulfield, Mike
Spiro, Emma S
Starbird, Kate
author_facet Schafer, Joseph S
Duskin, Kayla
Prochaska, Stephen
Wack, Morgan
Beers, Anna
Bozarth, Lia
Agajanian, Taylor
Caulfield, Mike
Spiro, Emma S
Starbird, Kate
contents Understanding the spread of online rumors is a pressing societal challenge and an active area of research across domains. In the context of the 2022 U.S. midterm elections, one influential social media platform for sharing information -- including rumors that may be false, misleading, or unsubstantiated -- was Twitter (now renamed X). To increase understanding of the dynamics of online rumors about elections, we present and analyze a dataset of 1.81 million Twitter posts corresponding to 135 distinct rumors which spread online during the midterm election season (September 5 to December 1, 2022). We describe how this data was collected, compiled, and supplemented, and provide a series of exploratory analyses along with comparisons to a previously-published dataset on 2020 election rumors. We also conduct a mixed-methods analysis of three distinct rumors about the election in Arizona, a particularly prominent focus of 2022 election rumoring. Finally, we provide a set of potential future directions for how this dataset could be used to facilitate future research into online rumors, misinformation, and disinformation.
format Preprint
id arxiv_https___arxiv_org_abs_2407_16051
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ElectionRumors2022: A Dataset of Election Rumors on Twitter During the 2022 US Midterms
Schafer, Joseph S
Duskin, Kayla
Prochaska, Stephen
Wack, Morgan
Beers, Anna
Bozarth, Lia
Agajanian, Taylor
Caulfield, Mike
Spiro, Emma S
Starbird, Kate
Social and Information Networks
Computers and Society
Understanding the spread of online rumors is a pressing societal challenge and an active area of research across domains. In the context of the 2022 U.S. midterm elections, one influential social media platform for sharing information -- including rumors that may be false, misleading, or unsubstantiated -- was Twitter (now renamed X). To increase understanding of the dynamics of online rumors about elections, we present and analyze a dataset of 1.81 million Twitter posts corresponding to 135 distinct rumors which spread online during the midterm election season (September 5 to December 1, 2022). We describe how this data was collected, compiled, and supplemented, and provide a series of exploratory analyses along with comparisons to a previously-published dataset on 2020 election rumors. We also conduct a mixed-methods analysis of three distinct rumors about the election in Arizona, a particularly prominent focus of 2022 election rumoring. Finally, we provide a set of potential future directions for how this dataset could be used to facilitate future research into online rumors, misinformation, and disinformation.
title ElectionRumors2022: A Dataset of Election Rumors on Twitter During the 2022 US Midterms
topic Social and Information Networks
Computers and Society
url https://arxiv.org/abs/2407.16051