A Higher-Order Temporal H-Index for Evolving Networks

Lutz Oettershagen, Nils Morten Kriege, Petra Mutzel

Veröffentlichungen: Beitrag in BuchBeitrag in KonferenzbandPeer Reviewed

Abstract

The H-index of a node in a static network is the maximum value h such that at least h of its neighbors have a degree of at least h. Recently, a generalized version, the n-th order H-index, was introduced, allowing to relate degree centrality, H-index, and the k-core of a node. We extend the n-th order H-index to temporal networks and define corresponding temporal centrality measures and temporal core decompositions. Our n-th order temporal H-index respects the reachability in temporal networks leading to node rankings, which reflect the importance of nodes in spreading processes. We derive natural decompositions of temporal networks into subgraphs with strong temporal coherence. We analyze a recursive computation scheme and develop a highly scalable streaming algorithm. Our experimental evaluation demonstrates the efficiency of our algorithms and the conceptional validity of our approach. Specifically, we show that the n-th order temporal H-index is a strong heuristic for identifying possible super-spreaders in evolving social networks and detects temporally well-connected components.
OriginalspracheEnglisch
TitelProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
ErscheinungsortNew York
Herausgeber (Verlag)Association for Computing Machinery (ACM)
Seiten1770-1782
Seitenumfang13
ISBN (Print)979-8-4007-0103-0
DOIs
PublikationsstatusVeröffentlicht - 6 Aug. 2023
Veranstaltung29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining - Long Beach, CA, USA / Vereinigte Staaten
Dauer: 6 Aug. 202310 Aug. 2023
https://kdd.org/kdd2023/

Publikationsreihe

ReiheACM Conferences
Band2023

Konferenz

Konferenz29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Land/GebietUSA / Vereinigte Staaten
OrtLong Beach, CA
Zeitraum6/08/2310/08/23
Internetadresse

ÖFOS 2012

  • 102019 Machine Learning

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