Proceedings of the International AAAI Conference on Web and Social Media · 2021 · 51 citations · 17 references
ComputingData ScienceInformation RetrievalKnowledge NetworksNetwork VisualizationNetwork MotifsScholarly EditingSocial Network AnalysisSocial NetworksTrend DetectionVersion ControlBipartite Network StructureBipartite NetworksCollaborative Document EditingRevision GraphsRevision History AnalysisRevisionsTemporal MotifsTemporal Network Motifs
Wikipedia is a collaborative setting with both combative and cooperative editing. We propose a new method for investigating the types of editor interactions using a novel representation of Wikipedia's revision history as a temporal, bipartite network with multiple node and edge types for users and revisions. From this representation we identify significant author interactions as network motifs and show how the motif types capture important, diverse editing behaviors. Two experiments demonstrate the further benefit of motifs. First, we demonstrate significant performance improvement over a purely revision-based analysis in classifying pages as combative or cooperative page by using motifs; and second we use motifs as a basis for analyzing trends in the dynamics of editor behavior to explain Wikipedia's content growth.
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