Israel-Hamas War on X: A Case Study of Coordinated Campaigns and Information Integrity

TL;DR

This study analyzes social media coordination during the 2023 Israel-Hamas War, revealing low-complexity tactics, fragmented narratives, and insights for targeted moderation to combat misinformation.

Contribution

It provides a detailed multimodal analysis of coordinated campaigns on Twitter during a conflict, highlighting tactics, narratives, and implications for moderation strategies.

Findings

Coordinated campaigns mainly use simple tactics like retweets and copy-paste diffusion.

Misleading claims are concentrated within a few coordinated groups.

Targeting prolific spreaders of misinformation can effectively reduce false content.

Abstract

Coordinated campaigns on social media play a critical role in shaping crisis information environments, particularly during the onset of conflicts when uncertainty is high and verified information is scarce. We study the interplay between coordinated campaigns and information integrity through a case study of the 2023 Israel-Hamas War on Twitter (X). We analyze 4.5~million tweets and employ established coordination detection methods to identify 11 coordinated groups involving 541 accounts. We characterize these groups through a multimodal analysis that includes topics, account amplification, toxicity, emotional tone, visual themes, and misleading claims. Our analysis reveal that coordinated campaigns rely predominantly on low-complexity tactics, such as retweet amplification and copy-paste diffusion, and promote distinct narratives consistent with a fragmented manipulation landscape, without centralized control. Widely amplified misleading claims concentrate within just three of the identified coordinated groups; the remaining groups primarily engage in advocacy, religious solidarity, or humanitarian mobilization. Claim-level integrity, toxicity, and emotional signals are mutually uncorrelated: no single behavioral signal is a reliable proxy for the others. Targeting the most prolific spreaders of misleading content for moderation would be effective in reducing such content. However, targeting prolific amplifiers in general would not achieve the same mitigation effect. These findings suggest that evaluating coordination structures jointly with their specific content footprints is needed to effectively prioritize moderation interventions.