Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior

Excerpt

arXiv:2608.16323v1 Announce Type: cross Abstract: The spread of misinformation on social networks poses a significant challenge to online communities and society at large. Not all users contribute equally to this phenomenon: a small number of highly effective individuals can exert outsized influence, amplifying false narratives and contributing to significant societal harm. This paper seeks to mitigate the spread of misinformation by enabling proactive interventions, identifying and ranking user