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Examining the Impact of Toxicity on Community Structure in Social Networks

Authors:
Niloofar Yousefi
Nitin Agarwal
Karen Watts DiCicco
Md. Samin Morshed

Keywords: Toxicity; Community dynamics; Social network; Granger causality; Network analysis; Community structure

Abstract:
Social media platforms, such as X continue to increase efforts to reduce harmful content, such as hate speech due to their impact on communities. The increase in harmful content was even more noticeable in 2020 with COVID-19 topics. This research systematically examines the impact of toxicity on the dynamics of communities on X, such as pro-vaccine, anti-vaccine COVID-19. Toxicity score calculated and social network analysis was performed to extract communities. These factors were co-analyzed to understand if the communities become more cohesive or more fractured over time with varying toxicity levels using Granger causality test. Our results demonstrate that in the pro-vaccine dataset, toxicity has a more substantial effect on community dynamics by fracturing communities as toxicity increases, whereas in the anti-vaccine dataset toxicity does not affect the community dynamics as much. These results have implications for how social media platforms can better moderate content and reduce toxicity within communities.

Pages: 17 to 22

Copyright: Copyright (c) IARIA, 2024

Publication date: September 29, 2024

Published in: conference

ISSN: 2326-9294

ISBN: 978-1-68558-198-5

Location: Venice, Italy

Dates: from September 29, 2024 to October 3, 2024