CS_TOTR: A new vertex centrality method for directed signed networks based on status theory

Yue Ma (), Min Liu (), Peng Zhang () and Xingqin Qi
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Yue Ma: School of Mathematics and Statistics, Shandong University (Weihai), Weihai, P. R. China
Min Liu: School of Mathematics and Statistics, Shandong University (Weihai), Weihai, P. R. China
Peng Zhang: School of Mathematics and Statistics, Shandong University (Weihai), Weihai, P. R. China
Xingqin Qi: School of Mathematics and Statistics, Shandong University (Weihai), Weihai, P. R. China

International Journal of Modern Physics C (IJMPC), 2018, vol. 29, issue 05, 1-16

Abstract: Measuring the importance (or centrality) of vertices in a network is a significant topic in complex network analysis, which has significant applications in diverse domains, for example, disease control, spread of rumors, viral marketing and so on. Existing studies mainly focus on social networks with only positive (or friendship) relations, while signed networks with also negative (or enemy) relations are seldom studied. Various signed networks commonly exist in real world, e.g. a network indicating friendship/enmity, love/hate or trust/mistrust relationships. In this paper, we propose a new centrality method named CS_TOTR to give a ranking of vertices in directed signed networks. To design this new method, we use the “status theory” for signed networks, and also adopt the vertex ranking algorithm for a tournament and the topological sorting algorithm for a general directed graph. We apply this new centrality method on the famous Sampson Monastery dataset and obtain a convincing result which shows its validity.

Keywords: Signed network; status theory; centrality method; topological sorting; tournament ranking (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0129183118400028

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