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Empirical Analysis of Centrality Characteristics in Real Online Social Networks

並列摘要


In this paper, we analyzed topological characteristics of four famous centrality indexes (including degree, closeness, betweenness, and the k-core) and their correlations (including Pearson correlation and Kendall Rank correlation) in two real data sets. It’s the fundamental work of identifying the influential nodes in complex networks. After simulations on two real data sets, we found that the distribution of degree, betweenness, and the k-core totally follow the power-law distribution. The Pearson correlation between degree and betweenness is the highest, however, the Kendall Rank Correlation between degree and k-core is relatively larger than values between degree and other two indexes.

被引用紀錄


陳婷婷(2010)。以氧氣電漿蝕刻的鑽石奈米管之場發特性研究〔碩士論文,國立清華大學〕。華藝線上圖書館。https://doi.org/10.6843/NTHU.2010.00284

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