文献类型：期刊文献

英文题名：How people make friends in social networking sites-A microscopic perspective

作者：Hu, Haibo[1];Wang, Xiaofan[2]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Complex Networks & Control Lab, Shanghai 200240, Peoples R China

年份：2012

卷号：391

期号：4

起止页码：1877

外文期刊名：PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

收录：;EI(收录号：20120114653015);WOS:【SSCI(收录号:WOS:000300459700093)，SCI-EXPANDED(收录号:WOS:000300459700093)】；

基金：We thank Wealink Co. for providing the network data. This work was partly supported by Major State Basic Research Development Program of China (No. 2010CB731400), National Natural Science Foundation of China (Nos. 61104139 and 70871039) and a grant from ECUST for excellent young scientists.

语种：英文

外文关键词：Online social network; Microscopic behavior; Reciprocation; Human dynamics; Preference

摘要：We study the detailed growth of a social networking site with full temporal information by examining the creation process of each friendship relation that can collectively lead to the macroscopic properties of the network. We first study the reciprocal behavior of users, and find that link requests are quickly responded to and that the distribution of reciprocation intervals decays in an exponential form. The degrees of inviters/accepters are slightly negatively correlative with reciprocation time. In addition, the temporal feature of the online community shows that the distributions of intervals of user behaviors, such as sending or accepting link requests, follow a power law with a universal exponent, and peaks emerge for intervals of an integral day. We finally study the preferential selection and linking phenomena of the social networking site and find that, for the former, a linear preference holds for preferential sending and reception, and for the latter, a linear preference also holds for preferential acceptance, creation, and attachment. Based on the linearly preferential linking, we put forward an analyzable network model which can reproduce the degree distribution of the network. The research framework presented in the paper could provide a potential insight into how the micro-motives of users lead to the global structure of online social networks. (C) 2011 Elsevier B.V. All rights reserved.