AI RESEARCH
HawkesRank: Event-Driven Centrality for Real-Time Importance Ranking
arXiv CS.LG
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ArXi:2603.11472v1 Announce Type: cross Quantifying influence in networks is important across science, economics, and public health, yet widely used centrality measures remain limited: they rely on static representations, heuristic network constructions, and purely endogenous notions of importance, while offering little semantic connection to observable activity. We