SIAILGAug 28, 2023

Detecting Inactive Cyberwarriors from Online Forums

arXiv:2308.15491v13 citationsh-index: 17Has Code
Originality Incremental advance
AI Analysis

This addresses the problem of misinformation warfare for cybersecurity and social media analysts, but it is incremental as it builds on existing detection methods by focusing on inactive phases.

The study tackled the problem of detecting cyberwarriors in online forums, finding that only a small fraction are active users, with most remaining silent during peacetime and acting only when necessary, and that identifying inactive cyberwarriors is more challenging than active ones.

The proliferation of misinformation has emerged as a new form of warfare in the information age. This type of warfare involves cyberwarriors, who deliberately propagate messages aimed at defaming opponents or fostering unity among allies. In this study, we investigate the level of activity exhibited by cyberwarriors within a large online forum, and remarkably, we discover that only a minute fraction of cyberwarriors are active users. Surprisingly, despite their expected role of actively disseminating misinformation, cyberwarriors remain predominantly silent during peacetime and only spring into action when necessary. Moreover, we analyze the challenges associated with identifying cyberwarriors and provide evidence that detecting inactive cyberwarriors is considerably more challenging than identifying their active counterparts. Finally, we discuss potential methodologies to more effectively identify cyberwarriors during their inactive phases, offering insights into better capturing their presence and actions. The experimental code is released for reproducibility: \url{https://github.com/Ryaninthegame/Detect-Inactive-Spammers-on-PTT}.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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