DocumentCode :
2901471
Title :
On the dynamics of influence networks via reflected appraisal
Author :
Peng Jia ; Mirtabatabaei, Anahita ; Friedkin, Noah E. ; Bullo, Francesco
Author_Institution :
Center for Control, Dynamical Syst. & Comput., Univ. of California at Santa Barbara, Santa Barbara, CA, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
1249
Lastpage :
1254
Abstract :
In any modern society, individuals interact to form opinions on various topics, including economic, political, and social aspects. Opinions evolve as the result of the continuous exchange of information among individuals where interpersonal influences play the key role. The study of influence network evolution has wide applications in the field of social organization and social psychology. A compelling model is Friedkin´s reflected appraisal model where each individual´s self-appraisal is set equal to the relative control and power that the agent exerted over prior issue outcomes. Motivated by this empirical framework, we (i) present a rigorous mathematical formulation of the reflected appraisal influence network dynamics, (ii) study the equilibria and the convergence properties of the dynamical influence systems, and (iii) construct the social conditions leading to the emergence of single opinion leaders, clusters of leaders, or diffuse and democratic power structures. In particular, an appropriately-defined eigenvector centrality of the influence network is proved to determine each individual´s social power and self-appraisal evolution, and then determine the opinion formulation of the whole network.
Keywords :
eigenvalues and eigenfunctions; psychology; social sciences; dynamical influence system; economic aspect; eigenvector centrality; influence network evolution; interpersonal influence; opinion formulation; political aspect; reflected appraisal influence network dynamics; reflected appraisal model; self-appraisal evolution; social aspect; social organization; social power; social psychology; Analytical models; Appraisal; Mathematical model; Stochastic processes; Topology; Trajectory; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580007
Filename :
6580007
Link To Document :
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