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25.10.2019 | Focus

Influence measures in subnetworks using vertex centrality

verfasst von: Roy Cerqueti, Gian Paolo Clemente, Rosanna Grassi

Erschienen in: Soft Computing | Ausgabe 12/2020

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Abstract

This work deals with the issue of assessing the influence of a node in the entire network and in the subnetwork to which it belongs as well, adapting the classical idea of vertex centrality. We provide a general definition of relative vertex centrality measure with respect to the classical one, referred to the whole network. Specifically, we give a decomposition of the relative centrality measure by including also the relative influence of the single node with respect to a given subgraph containing it. The proposed measure of relative centrality is tested in the empirical networks generated by collecting assets of the \( S \& P\) 100, focusing on two specific centrality indices: betweenness and eigenvector centrality. The analysis is performed in a time perspective, capturing the assets influence, with respect to the characteristics of the analysed measures, in both the entire network and the specific sectors to which the assets belong.

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For a detailed treatment we refer, for instance, to Harary (1969) and Newman (2010).

For many centrality measures proposed in the literature, a closed formula computing the centrality of a vertex in a complete graph \(K_n\) is provided.

Data have been downloaded from Bloomberg (2012).

In the empirical application, in a window t we disregard assets with a number of missing data higher than 20.

The normalized group betweenness can be obtained by dividing each value by the theoretical maximum, yielding to \(b'(G_s)= \frac{2b(G_s)}{(n-n_s)(n-n_s-1)}.\)

There exist other approaches in the literature to compute the centrality of a subset, such as, for instance, those proposed in Bonacich (1991).

Martin et al. (2014) overcome this issue providing a new centrality measure based on the leading eigenvector of the Hashimoto or non-backtracking matrix.

For a detailed description of sectors see, for instance, Appendix 1 in Beber et al (2011).

See Standard and Poor Factsheets, 2019.

See for instance “Wal-Mart Heirs See 11 Billion Vanish in a Day on Share Fall”, available at: https://web.archive.org/web/20151017210100/http://www.bloomberg.com/news/articles/2015-10-14/wal-mart-heirs-see-9-billion-vanish-in-a-day-as-shares-plummet.

Bristol-Myers has been the undisputed leader in immunotherapy, a new field of medicine that turns the body into a weapon against cancer. The company felt more than 16% after the company announced that its drug, Opdivo, had failed to significantly boost the amount of lifetime and quality of life of a type of lung cancer patients, compared to chemotherapy.

Battiston S, Glattfelder JB, Garlaschelli D, Lillo F, Caldarelli G (2010) The structure of financial networks. In: Network Science, Springer, Berlin, pp 131–163

Beber A, Brandt MW, Kavajecz KA (2011) What does equity sector orderflow tell us about the economy? Rev Financ Stud 24(11):3688–3730CrossRef

Benzi M, Klymko C (2015) On the limiting behavior of parameter-dependent network centrality measures. SIAM J Matrix Anal Appl 36:686–706MathSciNetMATHCrossRef

Bloomberg (2012) Bloomberg professional. [online]. Available at: Subscription Service (Accessed 30 Nov 2012)

Bonacich P (1972) Factoring and weighting approaches to status scores and clique identification. J Math Sociol 2(1):113–120CrossRef

Bonacich P (1987) Power and centrality: a family of measures. Am J Sociol 92:1170–1182CrossRef

Bonacich P (1991) Simultaneous group and individual centralities. Soc Netw 13(2):155–168CrossRef

Borgatti SP, Carley KM, Krakhardt D (2006) On the robustness of centrality measures under conditions of imperfect data. Soc Netw 28(2):124–136CrossRef

Cerqueti R, Ferraro G, Iovanella A (2018) A new measure for community structures through indirect social connections. Exp Syst Appl 114:196–209CrossRef

Cinelli M, Ferraro G, Iovanella A (2017a) Structural bounds on the dyadic effect. J Complex Netw 5(5):694–711MATHCrossRef

Cinelli M, Ferraro G, Iovanella A (2017b) Resilience of core-periphery networks in the case of rich-club. Complexity Article ID 6548362

Cinelli M, Ferraro G, Iovanella A (2018) Rich-club ordering and the dyadic effect: two interrelated phenomena. Phys A Stat Mech Appl 490:808–818CrossRef

Colizza V, Flammini A, Serrano MA, Vespignani A (2006) Detecting rich-club ordering in complex networks. Nat Phys 2(2):110CrossRef

Estrada E, Rodriguez-Velazquez JA (2005) Subgraph centrality in complex networks. Phys Rev E 71(5):056,103MathSciNetCrossRef

Everett MG, Borgatti SP (1999) The centrality of groups and classes. J Math Sociol 23(3):181–201MATHCrossRef

Freeman L (1979) Centrality in social networks—conceptual clarification. Soc Netw 1:215–239CrossRef

Freeman LC (1977) A set of measures of centrality based on betweenness. Sociometry 40(1):35–41CrossRef

Freeman S, Freeman L (1979) The networkers network: a study of the impact of a new communications medium on sociometric structure. Soc Sci Res Reports 46(103):109–115

Harary F (1969) Graph theory. Addison-Wesley, BostonMATHCrossRef

Katz L (1953) A new status index derived from sociometric analysis. Psychometrika 18(1):39–43MATHCrossRef

Landherr A, Friedl B, Heidemann J (2010) A critical review of centrality measures in social networks. Bus Inf Syst Eng 2(6):371–385CrossRef

Ma Q, Ma J (2019) A robust method to discover influential users in social networks. Soft Comput 23:1283–1295CrossRef

Martin T, Zhang X, Newman MEJ (2014) Localization and centrality in networks. Phys Rev E 90(5)

Newman M (2010) Networks: an introduction. Oxford University Press, OxfordMATHCrossRef

Opsahl T, Colizza V, Panzarasa P, Ramasco J (2008) Prominence and control: the weighted rich-club effect. Phys Rev Lett 110(18):189903CrossRef

Peralta G, Zareei A (2016) A network approach to portfolio selection. J Empir Financ 38(A):157–180CrossRef

Perra N, Fortunato S (2008) Spectral centrality measures in complex networks. Phys Rev E 78(3):036,107MathSciNetCrossRef

Pozzi F, Di Matteo T, Aste T (2013) Spread of risk across financial markets: better to invest in the peripheries. Scientific reports 3

Wang J, Mo H, Wang F, Jin F (2011) Exploring the network structure and nodal centrality of china’s air transport network: a complex network approach. J Transp Geogr 19(4):712–721CrossRef

Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, New YorkMATHCrossRef

Watts DJ (2004) Small worlds: the dynamics of networks between order and randomness, vol 9. Princeton University Press, PrincetonMATH

Titel: Influence measures in subnetworks using vertex centrality
verfasst von: Roy Cerqueti
Gian Paolo Clemente
Rosanna Grassi
Publikationsdatum: 25.10.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 12/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-04428-y

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