在线社交活动中的用户画像及其信息传播行为研究

Research on User Portrayal and Information Dissemination Behavior in Online Social Activities

【目的/意义】大数据时代,社交媒体用户的碎片化信息痕迹为刻画在线社交活动中的用户画像并揭示其信息传播行为提供了依据。【方法/过程】通过对微博、QQ群、天涯论坛、人人网等社交平台的深入挖掘,构建了在线社交活动中的用户画像模型,并对其信息传播行为的时间统计特征进行实证分析。【结果/结论】研究结果表明,在社交媒体用户的发布行为中,时间间隔服从重尾分布,其活跃程度与幂指数正相关,与时间间隔宽度负相关;而时间间隔的重新标度方法则在一定程度上消除了不同活跃程度个体所造成的影响;在交互行为中,时间间隔服从重尾分布,可用幂指数近似刻画,交互行为表现出"强阵发"特征,在一定程度上存在预测性。

[Purpose/significance]In the era of big data,the fragmentation information traces of social media users provide a basis for portraying user persona and revealing information behavior in online social activities.[Method/process]Through data mining on social platforms such as micre-blog,QQ group,Tianya forum,Renren and so on,we build a user portrait model in online social activities,and make an empirical analysis on the temporal statistical characteristics of information release behavior and interaction behavior.[Result/conclusion]Results show that the time interval follows heavy tailed distribution,and its activity is positively correlated with power exponent and negatively related to the time interval width.In this paper,the rescale method of time interval is further analyzed,and to a certain extent,the influence of individuals is eliminated.In the interaction,the time interval obey heavy tailed distribution,can be described by exponential approximation. Interactive behavior has features of strong intermittency,which can be used to forecast to some extent.