Limitation of degree information for analyzing the interaction evolution in online social networks

Ke-Ke Shang, Wei-Sheng Yan and Xiao-Ke Xu ()
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Ke-Ke Shang: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, P. R. China
Wei-Sheng Yan: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, P. R. China
Xiao-Ke Xu: College of Information and Communication Engineering, Dalian Nationalities University, Dalian 116605, P. R. China

International Journal of Modern Physics C (IJMPC), 2014, vol. 25, issue 10, 1-10

Abstract: Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

Keywords: User types; network evolution; online social network; complex network; 89.75.Hc; 89.65.-s; 89.75.-k; 05.10.-a (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0129183114500569

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