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Community Detection with Metadata in a Network of Biographies of Western Art Painters
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In this work we look at the structure of the influences between Western art painters as revealed by their biographies on Wikipedia. We use a modified version of modularity maximisation with metadata to detect a partition of artists into communities based on their artistic genre and school in which they belong. We then use this community structure to discuss how influential artists reached beyond their own communities and had a lasting impact on others, by proposing modifications on standard centrality measures.
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On community structure in complex networks: challenges and opportunities
A position paper summarizing generative models, dynamic community detection, and community-aware immunization strategies, with the takeaway that exploiting community structure improves performance.
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