Literature DB >> 16906930

Structure and evolution of online social relationships: Heterogeneity in unrestricted discussions.

K-I Goh1, Y-H Eom, H Jeong, B Kahng, D Kim.   

Abstract

With the advancement in the information age, people are using electronic media more frequently for communications, and social relationships are also increasingly resorting to online channels. While extensive studies on traditional social networks have been carried out, little has been done on online social networks. Here we analyze the structure and evolution of online social relationships by examining the temporal records of a bulletin board system (BBS) in a university. The BBS dataset comprises of 1908 boards, in which a total of 7446 students participate. An edge is assigned to each dialogue between two students, and it is defined as the appearance of the name of a student in the from- and to-field in each message. This yields a weighted network between the communicating students with an unambiguous group association of individuals. In contrast to a typical community network, where intracommunities (intercommunities) are strongly (weakly) tied, the BBS network contains hub members who participate in many boards simultaneously but are strongly tied, that is, they have a large degree and betweenness centrality and provide communication channels between communities. On the other hand, intracommunities are rather homogeneously and weakly connected. Such a structure, which has never been empirically characterized in the past, might provide a new perspective on the social opinion formation in this digital era.

Entities:  

Year:  2006        PMID: 16906930     DOI: 10.1103/PhysRevE.73.066123

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  2 in total

1.  Empirical Studies on the Network of Social Groups: The Case of Tencent QQ.

Authors:  Zhi-Qiang You; Xiao-Pu Han; Linyuan Lü; Chi Ho Yeung
Journal:  PLoS One       Date:  2015-07-15       Impact factor: 3.240

2.  Empirical analysis and modeling of users' topic interests in online forums.

Authors:  Fei Xiong; Yun Liu
Journal:  PLoS One       Date:  2012-12-12       Impact factor: 3.240

  2 in total

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