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Creating context for social influence processes in multiplex networks

  • J. ANTONIO RIVERO OSTOIC (a1)

Abstract

This paper elaborates on two theories of social influence processes to multiplex network structures. First, cohesion influence is based on mutual communication made by different types of relations, and second comparison influence that is built on contrasting types of tie. While a system of bundles with a mutual character constitutes the setting for a multiplex network exposure measure within cohesion, comparison influence is defined algebraically through classes of actors in terms of a weakly balanced semiring structure that considers positive, negative, and also ambivalent types of tie. A case study with these approaches is made on an entrepreneurial community network with formal business relations, informal friendship ties, and perceived competition among the firms, and the methods are validated with the Sampson Monastery data set.

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Back, K. (1951). Influence through social communication. Journal of Abnormal and Social Psychology, 46 (1), 923.
Bakshy, E., Messing, S., & Adamic, L. (2015). Exposure to ideologically diverse news and opinion on facebook. Science, 348 (6239), 11301132.
Barrat, A., Barthélemy, M., & Vespignani, A. (2008). Dynamical processes on complex networks. Cambridge: Cambridge University Press.
Batagelj, V. (1994). Semirings for social networks analysis. Journal of Mathematical Sociology, 1 (19), 5368.
Berger, C. R., & Burgoon, M. (1998). Communications and social influence processes. Lansing, MI: Michigan State University Press.
Breiger, R. L., Boorman, S. A., & Arabie, P. (1975). An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. Journal of Mathematical Psychology, 12 (3), 328383.
Burt, R. S. (1987). Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology, 92 (6), 12871335.
Cartwright, D., & Harary, F. (1956). Structural balance: A generalization of heider's theory. Psychological Review, 63 (5), 277293.
Coleman, J. S., Katz, E., & Menzel, H. (1966). Medical innovation: A diffusion study. Indianapolis, IN: Bobbs-Merrill Co.
Davis, J. A. (1967). Clustering and structural balance in graphs. Human Relations, 20 (2), 181187.
De Domenico, M., Solé-Ribalta, A., Cozzo, E., Kivelä, M., Moreno, Y., Porter, M., . . . Arenas, A. (2013). Mathematical formulation of multi-layer networks. Physical Review X, 3, 041022.
de Nooy, W., Mrvar, A., & Batagelj, V. (2005). Exploratory social network analysis with pajek. Structural Analysis in the Social Sciences, vol 34. Cambridge: Cambridge University Press.
Doreian, P., & Mrvar, A. (2015). Structural balance and signed international relations. Journal of Social Structure, 2 (13), 149.
Doreian, P., Batagelj, V., & Ferligoj, A. (2004). Generalized blockmodeling. Structural Analysis in the Social Sciences, vol. 25. Cambridge: Cambridge University Press.
Estrada, E., & Benzi, M. (2014). Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E, 90, 042802.
Festinger, L. (1950). Informal social communication. Psychological Review, 57 (5), 271–82.
Fienberg, S. E., & Wasserman, S. (1981). Categorical data analysis of single sociometric relations. Sociological Methodology, 12 (1), 156192.
Fienberg, S. E., Meyer, M. M., & Wasserman, S. S. (1985). Statistical analysis of multiple sociometric relations. Journal of the American Statistical Association, 80 (389), 5167.
Flament, C. (1963). Applications of graph theory to group structure. Prentice-Hall series in Mathematical Analysis of Social Behavior. Upper Saddle River, NJ: Prentice-Hall.
Friedkin, N. E. (1984). Structural cohesion and equivalence explanations of social homogeneity. Sociological Methods & Research, 12 (3), 235261.
Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software–Practice & Experience, 21 (11), 11291164.
Gallagher, H., & Robins, G. (2015). Network statistical models for language learning contexts: Exponential random graph models and willingness to communicate. Language Learning, 65 (4), 929962.
Gansner, E. R., Koren, Y., & North, S. (2005). Graph drawing by stress majorization. In Graph Drawing: 12th International Symposium, gd 2004, New York, NY, USA, September 29–October 2, 2004, revised selected papers. Berlin Heidelberg: Springer. pp. 239250.
Harary, F., Norman, Z., & Cartwright, D. (1965). Structural models: An introduction to the theory of directed graphs. New York, NY: John Wiley & Sons.
Heider, F. (2013). The psychology of interpersonal relations. Oxfordshire: Taylor & Francis.
Holland, P. W., & Leinhardt, S. (1981). An exponential family of probability distributions for directed graphs (with discussion). Journal of the American Statistical Association, 76 (373), 3365.
Homans, G. C. (1961). Social behavior: Its elementary forms. New York, NY: Harcourt Brace.
Kivelä, M., Arenas, A., Barthélemy, M., Gleeson, J., Moreno, Y., & Porter, M. (2014). Multilayer networks. Journal of Complex Networks, 2 (3), 203271.
Lazarsfeld, P., Berelson, B., & Gaudet, H. (1948). The people's choice: How the voter makes up his mind in presidential campaigns. New York, NY: Columbia University Press.
Lazega, E. (2001). The collegial phenomenon: The social mechanisms of cooperation among peers in a corporate law partnership. Oxford: Oxford University Press.
Lazega, E., & Pattison, P. E. (1999). Multiplexity, generalized exchange and cooperation in organizations: A case study. Social Networks, 21 (1), 6790.
Leenders, R. T. A. J. (2002). Modeling social influence through network autocorrelation: Constructing the weight matrix. Social Networks, 24 (1), 2147.
Lorrain, F., & White, H. C. (1971). Structural equivalence of individuals in social networks. Journal of Mathematical Sociology, 1 (1), 4980.
Luce, R. D., & Perry, A. D. (1949). A method of matrix analysis of group structure. Psychometrika, 2 (14), 95116.
Lusher, D., Koskinen, J., & Robins, G. (2013). Exponential random graph models for social networks: Theory, methods, and applications. Structural Analysis in the Social Sciences, vol. 35. Cambridge: Cambridge University Press.
McKnight, L. W., Vaaler, P. M., & Katz, R. L. (2002). Creative destruction: Business survival strategies in the global internet economy. Cambridge: MIT Press.
Ostoic, J. A. R. (2016a). multigraph: Plot and Manipulate Multigraphs. R package devel version 0.45.
Ostoic, J. A. R. (2016b). multiplex: Algebraic Tools for the Analysis of Multiple Social Networks. R package version 2.4.1.
Ostoic, J. A. R. (2013). Algebraic methods for the analysis of multiple social networks and actors attributes. Ph.D. thesis, University of Southern Denmark.
R Core Team. (2015). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/.
Rogers, E. (2003). The diffusion of innovations. 5th edn. (1st edn. 1964). New York, NY: The Free Press.
Ryan, R., & Gross, N. (1943). The diffusion of hybrid seed corn in two iowa communities. Rural Sociology, 1 (8), 1524.
Salehi, M., Sharma, R., Marzolla, M., Magnani, M., Siyari, P., & Montesi, D. (2015). Spreading processes in multilayer networks. IEEE Transactions on Network Science and Engineering, 2 (2), 6583.
Sampson, F. S. (1969). A novitiate in a period of change: An experimental and case study of social relationships. Ph.D. thesis, Cornell University.
Simmel, G., & Wolff, K. H. (1950). The sociology of Georg Simmel. New York, NY: Free Press.
Snijders, T. A. B., Pattison, P. E., Robins, G. L., & Handcock, M. S. (2006). New specifications for exponential random graph models. Sociological Methodology, 36 (99), 99153.
Strang, D., & Tuma, N. B. (1993). Spatial and temporal heterogeneity in diffusion. American Journal of Sociology, 3 (99), 614639.
Valente, T. W. (2010). Social networks and health. Oxford: Oxford University Press.
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Structural Analysis in the Social Sciences, vol. 8. Cambridge: Cambridge University Press.
Wellman, B. (1988). Structural analysis: From method and metaphor to theory and substance. Chap. 1, In Wellman, B., & Berkowitz, S. D. (Eds.), Social structures: A network approach (pp. 1961). Cambridge: Cambridge University Press.
White, H. C., Boorman, S. A., & Breiger, R. L. (1976). Social structure from multiple networks I: Blockmodels of roles and positions. American Journal of Sociology, 81 (4), 730780.

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Creating context for social influence processes in multiplex networks

  • J. ANTONIO RIVERO OSTOIC (a1)

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