The influence of coordinated behavior on toxicity

In the intricate landscape of social media, genuine content dissemination may be altered by a number of threats. Coordinated Behavior (CB), defined as orchestrated efforts by entities to deceive or mislead users about their identity and intentions, emerges as a tactic to exploit or manipulate online discourse. This study delves into the relationship between CB and toxic conversation on X (formerly known as Twitter). Using a dataset of 11 million tweets from 1 million users preceding the 2019 UK general election, we show that users displaying CB typically disseminate less harmful content, irrespective of political affiliation. However, distinct toxicity patterns emerge among different coordinated cohorts. Compared to their non-CB counterparts, CB participants show marginally higher toxicity levels only when considering their original posts. We further show the effects of CB-driven toxic content on non-CB users, gauging its impact based on political leanings. Our findings suggest that CB only has a limited impact on the toxicity of digital discourse.

Authors

Institutions

Publication Details

Journal
Online Social Networks and Media
Published
2024-10-03
DOI
https://doi.org/10.1016/j.osnem.2024.100289
Citations
6
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
6.79
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The influence of coordinated behavior on toxicity

Walter Quattrociocchi, Maurizio Tesconi, Matteo Cinelli, Edoardo Loru
6 citations
Online Social Networks and Media
Misinformation and Its Impacts
6.79
article

The influence of coordinated behavior on toxicity

Walter Quattrociocchi, Maurizio Tesconi, Matteo Cinelli, Edoardo Loru
article en
6 citations

Abstract

In the intricate landscape of social media, genuine content dissemination may be altered by a number of threats. Coordinated Behavior (CB), defined as orchestrated efforts by entities to deceive or mislead users about their identity and intentions, emerges as a tactic to exploit or manipulate online discourse. This study delves into the relationship between CB and toxic conversation on X (formerly known as Twitter). Using a dataset of 11 million tweets from 1 million users preceding the 2019 UK general election, we show that users displaying CB typically disseminate less harmful content, irrespective of political affiliation. However, distinct toxicity patterns emerge among different coordinated cohorts. Compared to their non-CB counterparts, CB participants show marginally higher toxicity levels only when considering their original posts. We further show the effects of CB-driven toxic content on non-CB users, gauging its impact based on political leanings. Our findings suggest that CB only has a limited impact on the toxicity of digital discourse.

Online Social Networks and MediaVol. 43-44
Institute of Informatics and Telematics (IT), Sapienza University of Rome (IT)
Zero hunger
Openalex Percentile: Top 3%
Misinformation and Its Impacts
6.79
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.