Multimodal Coordinated Online Behavior: Trade-offs and Strategies
Lorenzo Mannocci, Stefano Cresci, Matteo Magnani, Anna Monreale, Maurizio Tesconi

TL;DR
This paper compares different multimodal approaches to detecting coordinated online behavior, highlighting that multimodal analysis provides more comprehensive insights than monomodal methods, thereby improving detection of complex coordination patterns.
Contribution
It systematically evaluates various strategies for operationalizing multimodal coordination, revealing the advantages of integrated multimodal analysis over monomodal and flattened approaches.
Findings
Multimodal analysis captures more coordination structures.
Not all modalities contribute equally to insights.
Integrated models outperform monomodal methods.
Abstract
Coordinated online behavior, which spans from beneficial collective actions to harmful manipulation such as disinformation campaigns, has become a key focus in digital ecosystem analysis. Traditional methods often rely on monomodal approaches, focusing on single types of interactions like co-retweets or co-hashtags, or consider multiple modalities independently of each other. However, these approaches may overlook the complex dynamics inherent in multimodal coordination. This study compares different ways of operationalizing multimodal coordinated behavior, examining the trade-off between weakly and strongly integrated models and their ability to capture broad versus tightly aligned coordination patterns. By contrasting monomodal, flattened, and multimodal methods, we evaluate the distinct contributions of each modality and the impact of different integration strategies. Our findings…
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Taxonomy
TopicsMisinformation and Its Impacts · Opinion Dynamics and Social Influence · Complex Network Analysis Techniques
