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Coordinated online behaviors are an essential part of information andinfluence operations, as they allow a more effective disinformation's spread.Most studies on coordinated behaviors involved manual investigations, and thefew existing computational approaches make bold assumptions or oversimplify theproblem to make it tractable. Here, we propose a new network-based frameworkfor uncovering and studying coordinated behaviors on social media. Our researchextends existing systems and goes beyond limiting binary classifications ofcoordinated and uncoordinated behaviors. It allows to expose differentcoordination patterns and to estimate the degree of coordination thatcharacterizes diverse communities. We apply our framework to a datasetcollected during the 2019 UK General Election, detecting and characterizingcoordinated communities that participated in the electoral debate. Our workconveys both theoretical and practical implications and provides more nuancedand fine-grained results for studying online information manipulation.

Coordinated Behavior on Social Media in 2019 UK General Election