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arXiv · 2610.17533

A null model to detect coordinated online behavior integrating evidence from multiple indicators

Filipi Nascimento Silva·Manita Pote·Lake Yin·Luca Luceri·Filippo Menczer·Alessandro Flammini
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Abstract

Coordinated online accounts can amplify messages and manipulate attention, but detecting such behavior is challenging due to confounding factors like account activity and item popularity. We propose a statistical null-model framework that assesses behavioral similarity between accounts by comparing observed coordination indicators against activity- and popularity-conditioned reference distributions. By combining evidence across multiple indicators and partners, our method can identify suspicious coordination links more accurately. Evaluations on nine labeled information-operation datasets involving over 152 thousand accounts show that aggregating p-values multiplicatively across indicators and partners yields improved detection performance. While results vary across information operations, this approach offers a generalizable and statistically principled tool for uncovering coordinated online behavior.

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Filipi Nascimento Silva, Manita Pote, Lake Yin, Luca Luceri, Filippo Menczer, Alessandro Flammini. 2026-10-13. A null model to detect coordinated online behavior integrating evidence from multiple indicators. https://arxiv.org/abs/2610.17533

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