社交网络站点社群信息过载的影响因素研究——加权小世界网络视角的分析

Research on the Factors influencing the Information Overload in Social Network Sites' Communities——Based on Weighted Small-world Network Model

基于加权小世界网络理论,以人人网为实验平台,分析目前社交网络站点信息内容积累困难、"信息孤岛"现象泛滥导致的用户获取信息重复率高、同质化高的现状及其解决方式。在利用社会网络站点成员间的特征关系长度和聚类系数来表征社会网络站点的信息传播频率、集中度时,发现当这些要素保持在一个特定的水平时,才能有效地促进社群的信息传播与获取。

The dissertation is based on Weighted Small-world Network Model. We use Renren.com as theexperimental platform aiming to analyze and deal with the situation that the high rate of the identicalinformation which received by the users of social network sites＇ communities is caused by the difficulty inaccumulating the information in social network sites and the phenomenon of‘isolated islands ofinformation＇. Putting forward the idea for using characteristic relationship length and clusteringcoefficient of communities＇ members to token information diffusion frequency and centralizationrespectively, which must be kept at a specific level for better information spreading.