文献类型：期刊文献

英文题名：A generalized theory of preferential linking

作者：Hu, Haibo[1,2];Guo, Jinli[3];Liu, Xuan[1];Wang, Xiaofan[4]

机构：[1]E China Univ Sci & Technol, Shanghai 200237, Peoples R China;[2]City Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China;[3]Univ Shanghai Sci & Technol, Shanghai 200093, Peoples R China;[4]Shanghai Jiao Tong Univ, Shanghai 200240, Peoples R China

年份：2014

卷号：415

起止页码：544

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

收录：;EI(收录号：20144100093661);WOS:【SSCI(收录号:WOS:000343850400052)，SCI-EXPANDED(收录号:WOS:000343850400052)】；

基金：We thank the anonymous reviewers for their remarks and suggestions which helped us to improve the quality of the manuscript. We also thank Wealink Co. for providing the network data. A part of this work was finished at City University of Hong Kong when the first author was a Postdoctoral Fellow there. This work was partly supported by the National Natural Science Foundation of China (Nos. 61104139, 71101053, 71271087 and 61473119), the Fundamental Research Funds for the Central Universities (Nos. WN1223008 and WN1323006), the Hujiang Foundation of China (No. A14006), Shanghai First-class Academic Discipline Project (No. S1201YLXK) and HKRGC GRF (No. CityU 154412).

语种：英文

外文关键词：Online social network; Preferential linking; Network evolution; Model

摘要：There are diverse mechanisms driving the evolution of social networks. A key open question dealing with understanding their evolution is: How do various preferential linking mechanisms produce networks with different features? In this paper we first empirically study preferential linking phenomena in an evolving online social network, find and validate the linear preference. We propose an analyzable model which captures the real growth process of the network and reveals the underlying mechanism dominating its evolution. Furthermore based on preferential linking we propose a generalized model reproducing the evolution of online social networks, and present unified analytical results describing network characteristics for 27 preference scenarios. We study the mathematical structure of degree distributions and find that within the framework of preferential linking analytical degree distributions can only be the combinations of finite kinds of functions which are related to rational, logarithmic and inverse tangent functions, and extremely complex network structure will emerge even for very simple sublinear preferential linking. This work not only provides a verifiable origin for the emergence of various network characteristics in social networks, but bridges the micro individuals' behaviors and the global organization of social networks. (C) 2014 Elsevier B.V. All rights reserved.