Patterns of Incivility on U.S. Congress Members' Social Media Accounts
A Comprehensive Analysis of the Influence of Platform, Post, and Person Characteristics
Abstract #
With social media now being ubiquitously used by citizens and political actors, concerns over the incivility of interactions on these platforms have grown. While research has already started to investigate some of the factors that lead users to leave incivil comments on political social media posts, we are lacking a comprehensive understanding of the influence of platform, post, and person characteristics. Using automated text analysis methods on a large body of U.S. Congress Members’ social media posts (n = 253,884) and the associated user comments (n = 49,508,863), we investigate how different social media platforms (Facebook, Twitter), characteristics of the original post (e.g., incivility, reach), and personal characteristics of the politicians (e.g., gender, ethnicity) affect the occurrence of incivil user comments. Our results show that ~23% of all comments can be classified as incivil but that there are important temporal and contextual dynamics. Having incivil comments on one’s social media page seems more likely on Twitter than on Facebook and more likely when politicians use incivil language themselves, while the influence of personal characteristics is less clear-cut. Our findings add to the literature on political incivility by providing important insights regarding the dynamics of uncivil discourse, thus helping platforms, political actors, and educators to address associated problems.
Cite #
@article{
Unkel_2022,
title={Patterns of Incivility on U.S. Congress Members’ Social Media Accounts: A Comprehensive Analysis of the Influence of Platform, Post, and Person Characteristics},
volume={4},
ISSN={2673-3145},
url={http://dx.doi.org/10.3389/fpos.2022.809805},
DOI={10.3389/fpos.2022.809805},
journal={Frontiers in Political Science},
publisher={Frontiers Media SA},
author={Unkel, Julian and Kümpel, Anna Sophie},
year={2022}
}
Meta
- 2022
- English