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Lobby index as a network centrality measure

Author

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  • Campiteli, M.G.
  • Holanda, A.J.
  • Soares, L.D.H.
  • Soles, P.R.C.
  • Kinouchi, O.

Abstract

We study the lobby index (l-index for short) as a local node centrality measure for complex networks. The l-index is compared with degree (a local measure), betweenness and Eigenvector centralities (two global measures) in the case of a biological network (Yeast interaction protein–protein network) and a linguistic network (Moby Thesaurus II). In both networks, the l-index has a poor correlation with betweenness but correlates with degree and Eigenvector centralities. Although being local, the l-index carries more information about its neighbors than degree centrality. Also, it requires much less time to compute when compared with Eigenvector centrality. Results show that the l-index produces better results than degree and Eigenvector centrality for ranking purposes.

Suggested Citation

  • Campiteli, M.G. & Holanda, A.J. & Soares, L.D.H. & Soles, P.R.C. & Kinouchi, O., 2013. "Lobby index as a network centrality measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5511-5515.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:21:p:5511-5515
    DOI: 10.1016/j.physa.2013.06.065
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    References listed on IDEAS

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    1. Pablo D. Batista & Mônica G. Campiteli & Osame Kinouchi, 2006. "Is it possible to compare researchers with different scientific interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 179-189, July.
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    Cited by:

    1. Wen Zhou & Jiayi Gu & Yifan Jia, 2018. "h-Index-based link prediction methods in citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 381-390, October.
    2. Du, Yuxian & Gao, Cai & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "A new method of identifying influential nodes in complex networks based on TOPSIS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 57-69.

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