Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections

In this multi-platform, comparative study, we analyze social media messages from political candidates ( N = 1,517) running for Congress during the 2022 U.S. Midterm election. We collect data from seven social media platforms: Facebook, Twitter, Truth Social, Gettr, Instagram, YouTube, and Rumble over the 4 weeks before and after election day. With this unique dataset of posts, we apply computational methods to identify messages that sought to mobilize individuals (online and offline) to donate money, vote, attend events, engage with the campaign online, and visit the campaign’s content on other platforms. We find that Democrats were not on alt-tech platforms in 2022 and that both Republicans and Democrats use video-based platforms for multiple mobilization strategies. Mobilization messages varied for House and Senate candidates of both parties across platforms, before and after election day.

Authors

Institutions

Publication Details

Journal
Social Media + Society
Published
2025-04-01
DOI
https://doi.org/10.1177/20563051251337541
Citations
2
Primary Topic
Electoral Systems and Political Participation
Type
article
Field-Weighted Citation Impact
17.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections

Jiyoun Suk, Ross Dahlke, Stephen Prochaska, Wei Zhong et al.
2 citations
Social Media + Society
Electoral Systems and Political Participation
17.04
article

Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections

Jiyoun Suk, Ross Dahlke, Stephen Prochaska, Wei Zhong, Josephine Lukito, Megan A. Brown, Maggie Macdonald, Yunkang Yang, Porismita Borah, Bin Chen, Jason Greenfield
article en
2 citations

Abstract

In this multi-platform, comparative study, we analyze social media messages from political candidates ( N = 1,517) running for Congress during the 2022 U.S. Midterm election. We collect data from seven social media platforms: Facebook, Twitter, Truth Social, Gettr, Instagram, YouTube, and Rumble over the 4 weeks before and after election day. With this unique dataset of posts, we apply computational methods to identify messages that sought to mobilize individuals (online and offline) to donate money, vote, attend events, engage with the campaign online, and visit the campaign’s content on other platforms. We find that Democrats were not on alt-tech platforms in 2022 and that both Republicans and Democrats use video-based platforms for multiple mobilization strategies. Mobilization messages varied for House and Senate candidates of both parties across platforms, before and after election day.

Social Media + SocietyVol. 11(2)
University of Wisconsin–Madison (US), University of Connecticut (US), University of Kentucky (US), University of Washington (US), University of Michigan (US), New York University (US), Washington State University (US), The University of Texas at Austin (US), University of Hong Kong (HK), Texas A&M University (US)
Openalex Percentile: Top 2%
Electoral Systems and Political Participation
17.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.