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2017 | OriginalPaper | Buchkapitel

Comparative Study of Centrality Measures on Social Networks

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Abstract

Many centrality measures have been proposed to quantify importance of nodes within their network [1, 2]. This paper aims to compare fourteen of them: betweenness centrality, closeness centrality, communicability betweenness, cross clique centrality, in degree, out degree, diffusion degree, edge percolated component, eigenvector centrality, geodesic k-path, leverage centrality, lobby centrality, percolation centrality, semi-local centrality. Centralities are compared to their respective characteristics and with applications on two social networks. The first one is about communication within a terrorist cell [3], and the second concerns a sexually transmitted infection [4]. The main characteristics of each centrality measure have been identified. Centrality measures all succeed in identifying the most influential nodes on both networks. The results also show that measures slightly differ on non-predominant nodes.

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Literatur
1.
Zurück zum Zitat Jalili, M., Salehzadeh-Yazdi, A., Asgari, Y., Arab, S.S., Yaghmaie, M., Ghavamzadeh, A., Alimoghaddam, K.: CentiServer: a comprehensive resource, web-based application and R package for centrality analysis. PloS one 10(11), e0143111 (2015)CrossRef Jalili, M., Salehzadeh-Yazdi, A., Asgari, Y., Arab, S.S., Yaghmaie, M., Ghavamzadeh, A., Alimoghaddam, K.: CentiServer: a comprehensive resource, web-based application and R package for centrality analysis. PloS one 10(11), e0143111 (2015)CrossRef
2.
Zurück zum Zitat Borgatti, S.P., Everett, M.G.: A graph-theoretic perspective on centrality. Soc. Netw. 28(4), 466–484 (2006)CrossRef Borgatti, S.P., Everett, M.G.: A graph-theoretic perspective on centrality. Soc. Netw. 28(4), 466–484 (2006)CrossRef
3.
Zurück zum Zitat Azad, S., Gupta, A.: A quantitative assessment on 26/11 Mumbai attack using social network analysis. J. Terrorism Res. 2(2), 4–14 (2011)CrossRef Azad, S., Gupta, A.: A quantitative assessment on 26/11 Mumbai attack using social network analysis. J. Terrorism Res. 2(2), 4–14 (2011)CrossRef
4.
Zurück zum Zitat De, P., Singh, A.E., Wong, T., Yacoub, W., Jolly, A.M.: Sexual network analysis of a gonorrhoea outbreak. Sex. Transm. Infect. 80(4), 280–285 (2004)CrossRef De, P., Singh, A.E., Wong, T., Yacoub, W., Jolly, A.M.: Sexual network analysis of a gonorrhoea outbreak. Sex. Transm. Infect. 80(4), 280–285 (2004)CrossRef
5.
Zurück zum Zitat Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, New York (1994)CrossRefMATH Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, New York (1994)CrossRefMATH
6.
Zurück zum Zitat Otte, E., Rousseau, R.: Social network analysis: a powerful strategy, also for the information sciences. J. Inf. Sci. 28(6), 441–453 (2002)CrossRef Otte, E., Rousseau, R.: Social network analysis: a powerful strategy, also for the information sciences. J. Inf. Sci. 28(6), 441–453 (2002)CrossRef
7.
Zurück zum Zitat Newman, M.: Network: An Introduction, p. 784. OUP, Oxford (2009) Newman, M.: Network: An Introduction, p. 784. OUP, Oxford (2009)
8.
Zurück zum Zitat Latora, V., Marchiori, M.: Efficient behavior of small-world networks. Phys. Rev. Lett. 87(19), 198701 (2001)CrossRef Latora, V., Marchiori, M.: Efficient behavior of small-world networks. Phys. Rev. Lett. 87(19), 198701 (2001)CrossRef
9.
Zurück zum Zitat Estrada, E., Higham, D.J., Hatano, N.: Communicability betweenness in complex networks. Physica A Stat. Mech. Appl. 388(5), 764–774 (2009)CrossRef Estrada, E., Higham, D.J., Hatano, N.: Communicability betweenness in complex networks. Physica A Stat. Mech. Appl. 388(5), 764–774 (2009)CrossRef
10.
Zurück zum Zitat Faghani, M.R., Nguyen, U.T.: A study of XSS worm propagation and detection mechanisms in online social networks. IEEE Trans. Inf. Forensics Secur. 8(11), 1815–1826 (2013)CrossRef Faghani, M.R., Nguyen, U.T.: A study of XSS worm propagation and detection mechanisms in online social networks. IEEE Trans. Inf. Forensics Secur. 8(11), 1815–1826 (2013)CrossRef
11.
Zurück zum Zitat Kundu, S., Murthy, C.A., Pal, S.K.: A new centrality measure for influence maximization in social networks. In: Kuznetsov, S.O., Mandal, D.P., Kundu, M.K., Pal, S.K. (eds.) PReMI 2011. LNCS, vol. 6744, pp. 242–247. Springer, Heidelberg (2011). doi:10.1007/978-3-642-21786-9_40 CrossRef Kundu, S., Murthy, C.A., Pal, S.K.: A new centrality measure for influence maximization in social networks. In: Kuznetsov, S.O., Mandal, D.P., Kundu, M.K., Pal, S.K. (eds.) PReMI 2011. LNCS, vol. 6744, pp. 242–247. Springer, Heidelberg (2011). doi:10.​1007/​978-3-642-21786-9_​40 CrossRef
12.
Zurück zum Zitat Chin, C.S., Samanta, M.P.: Global snapshot of a protein interaction network - a percolation based approach. Bioinformatics 19(18), 2413–2419 (2003)CrossRef Chin, C.S., Samanta, M.P.: Global snapshot of a protein interaction network - a percolation based approach. Bioinformatics 19(18), 2413–2419 (2003)CrossRef
13.
Zurück zum Zitat Joyce, K.E., Laurienti, P.J., Burdette, J.H., Hayasaka, S.: A new measure of centrality for brain networks. PLoS One 5(8), e12200 (2010)CrossRef Joyce, K.E., Laurienti, P.J., Burdette, J.H., Hayasaka, S.: A new measure of centrality for brain networks. PLoS One 5(8), e12200 (2010)CrossRef
14.
Zurück zum Zitat Korn, A., Schubert, A., Telcs, A.: Lobby index in networks. Physica A Stat. Mech. Appl. 388(11), 2221–2226 (2009)CrossRef Korn, A., Schubert, A., Telcs, A.: Lobby index in networks. Physica A Stat. Mech. Appl. 388(11), 2221–2226 (2009)CrossRef
15.
Zurück zum Zitat Hamed, I., Charrad, M.: Recognizing information spreaders in terrorist networks: 26/11 attack case study. In: Bellamine Ben Saoud, N., Adam, C., Hanachi, C. (eds.) ISCRAM-med 2015. LNBIP, vol. 233, pp. 27–38. Springer, Cham (2015). doi:10.1007/978-3-319-24399-3_3 CrossRef Hamed, I., Charrad, M.: Recognizing information spreaders in terrorist networks: 26/11 attack case study. In: Bellamine Ben Saoud, N., Adam, C., Hanachi, C. (eds.) ISCRAM-med 2015. LNBIP, vol. 233, pp. 27–38. Springer, Cham (2015). doi:10.​1007/​978-3-319-24399-3_​3 CrossRef
16.
Zurück zum Zitat Piraveenan, M., Prokopenko, M., Hossain, L.: Percolation centrality: quantifying graph-theoretic impact of nodes during percolation in networks. PloS one 8(1), e53095 (2013)CrossRef Piraveenan, M., Prokopenko, M., Hossain, L.: Percolation centrality: quantifying graph-theoretic impact of nodes during percolation in networks. PloS one 8(1), e53095 (2013)CrossRef
17.
Zurück zum Zitat Chen, D., Linyuan, L., Shang, M.S., Zhang, Y.C., Zhou, T.: Identifying influential nodes in complex networks. Physica A Stat. Mech. Appl. 391(4), 1777–1787 (2012)CrossRef Chen, D., Linyuan, L., Shang, M.S., Zhang, Y.C., Zhou, T.: Identifying influential nodes in complex networks. Physica A Stat. Mech. Appl. 391(4), 1777–1787 (2012)CrossRef
18.
Zurück zum Zitat Koschtzki, D., Schreiber, F.: Comparison of centralities for biological networks. In: German Conference on Bioinformatics, pp. 199–206 (2004) Koschtzki, D., Schreiber, F.: Comparison of centralities for biological networks. In: German Conference on Bioinformatics, pp. 199–206 (2004)
19.
Zurück zum Zitat Kendall, M.G., Gibbons, J.D.: Rank Correlation Methods, p. 260. Edward Arnold, London (1990)MATH Kendall, M.G., Gibbons, J.D.: Rank Correlation Methods, p. 260. Edward Arnold, London (1990)MATH
Metadaten
Titel
Comparative Study of Centrality Measures on Social Networks
verfasst von
Nadia Ghazzali
Alexandre Ouellet
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-67633-3_1

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