DocumentCode :
266387
Title :
Evolutionary social information diffusion analysis
Author :
Chunxiao Jiang ; Yan Chen ; Liu, K. J. Ray
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
fYear :
2014
fDate :
8-12 Dec. 2014
Firstpage :
2911
Lastpage :
2916
Abstract :
Nowadays, social networks are extremely large-scale with tremendous information flows, where understanding how the information diffuse over social networks becomes an important research issue. Most of the existing works on information diffusion analysis are based on either network structure modeling or empirical approach with dataset mining. However, the information diffusion is also heavily influenced by network users´ decisions, actions and their socio-economic connections, which is generally ignored by existing works. In this paper, we propose an evolutionary game theoretic framework to model the dynamic information diffusion process in social networks. To verify our theoretical analysis, we conduct experiments by using Facebook network and real-world information spreading dataset of Memetracker. Experiment results show that the proposed game theoretic framework is effective and practical in modeling the social network users´ information forwarding behaviors.
Keywords :
game theory; graph theory; social networking (online); Facebook network; Memetracker; dynamic information diffusion process model; evolutionary game theoretic framework; evolutionary social information diffusion analysis; network user actions; network user decisions; real-world information spreading dataset; social network user information forwarding behaviors; socio-economic connections; Biological system modeling; Diffusion processes; Evolution (biology); Facebook; Games; Tin;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
Type :
conf
DOI :
10.1109/GLOCOM.2014.7037250
Filename :
7037250
Link To Document :
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