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原文連結
論文資訊
- 類型：已發表論文
- 日期：2008
摘要
To comprehend the multipartite organization of large-scale 生物 and 社會 systems, we introduce an 資訊 theoretic approach that reveals community structure in weighted and directed 網絡s. We use the probability flow of random walks on a 網絡 as a proxy for 資訊 flows in the real system and decompose the 網絡 into modules by compressing a description of the probability flow. The result is a map that both simplifies and highlights the regularities in the structure and their relationships. We illustrate the method by making a map of scientific communication as captured in the citation patterns of >6,000 journals. We discover a multicentric organization with fields that vary dramatically in size and degree of integration into the 網絡 of science. Along the backbone of the 網絡-including physics, chemistry, molec
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