DocumentCode :
630889
Title :
On new characterizations of social influence in social networks
Author :
Fardad, Mohammad ; Fu Lin ; Xi Zhang ; Jovanovic, Mihailo R.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., Syracuse, NY, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
4777
Lastpage :
4782
Abstract :
We propose new characterizations of social influence, which quantify both the transient and the steady-state propagation of beliefs across society. These characterizations are used to optimally choose a desired number of agents in a social network to serve as social leaders with maximal social impact. We then consider a framework for optimally creating new social links subject to resource constraints, in order to improve the influence of designated agents or social leaders. We show that the formulated optimization problems are convex with respect to the individual elements of the optimization variables. This motivates the use of the coordinate descent method, a simple but efficient algorithm well-suited to large-scale optimization problems. Finally, using demonstrative examples, we compare the ability of our proposed characterizations of social influence in identifying the most influential agents with that of other measures of influence developed in the social networks literature.
Keywords :
convex programming; social networking (online); belief steady-state propagation; belief transient propagation; convex optimization problems; coordinate descent method; influential agents; large-scale optimization problems; maximal social impact; resource constraints; social influence characterization; social leaders; social links; social networks; Artificial neural networks; Convergence; Eigenvalues and eigenfunctions; Linear programming; Optimization; Social network services; Vectors; Betweenness centrality; consensus; convex relaxation; coordinate descent; leader selection; optimization; social influence; social networks; sparsity; stochastic matrices;
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.2013.6580577
Filename :
6580577
Link To Document :
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