Beyond Content: Behavioral Policies Reveal Actors in Information Operations
Philipp J. Schneider, Lanqin Yuan, Marian-Andrei Rizoiu

TL;DR
This paper presents a behavioral policy-based framework for detecting malicious actors in online influence campaigns, outperforming content analysis, especially under evasion or data limitations.
Contribution
It introduces a novel, platform-agnostic approach modeling user activity as sequential decision processes to identify malicious actors.
Findings
Behavioral policies outperform content models in detection accuracy.
Policy classifiers achieve median macro-F1 of 94.9%.
Early detection is possible with short activity traces.
Abstract
The detection of online influence operations -- coordinated campaigns by malicious actors to spread narratives -- has traditionally depended on content analysis or network features. These approaches are increasingly brittle as generative models produce convincing text, platforms restrict access to behavioral data, and actors migrate to less-regulated spaces. We introduce a platform-agnostic framework that identifies malicious actors from their behavioral policies by modeling user activity as sequential decision processes. We apply this approach to 12,064 Reddit users, including 99 accounts linked to the Russian Internet Research Agency in Reddit's 2017 transparency report, analyzing over 38 million activity steps from 2015-2018. Activity-based representations, which model how users act rather than what they post, consistently outperform content models in detecting malicious accounts.…
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Taxonomy
TopicsSpam and Phishing Detection · Misinformation and Its Impacts · Cybercrime and Law Enforcement Studies
