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• W4207074113 abstract "Significance Community structure arising through relationships and interactions is essential to our understanding of the world around us. Leveraging social concepts of conflict and support, we introduce a method to transform input dissimilarity comparisons into output pairwise relationship strengths (or cohesion ) and resulting weighted networks. The introduced perspective may be particularly valuable for data with varying local density such as that arising from complex evolutionary processes. Mathematical results, together with applications in linguistics, genetics, and cultural psychology as well as to benchmark data, have been included. Together, these demonstrate how meaningful community structure can be identified without additional inputs (e.g., number of clusters or neighborhood size), optimization criteria, iterative procedures, or distributional assumptions." @default.
• W4207074113 created "2022-01-26" @default.
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• W4207074113 date "2022-01-21" @default.
• W4207074113 modified "2023-09-26" @default.
• W4207074113 title "A social perspective on perceived distances reveals deep community structure" @default.
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• W4207074113 doi "https://doi.org/10.1073/pnas.2003634119" @default.
• W4207074113 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35064077" @default.
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