社交网络活跃行为的大数据分析:网络外部性的视角

发布时间：2019-01-11 15:38

【摘要】：用户是社交网络平台的基石,用户的活跃行为为平台创造内容、带来价值,因而用户活跃度一直是社交网络平台的关注重点。已有研究仅关注用户是否存在持续使用意向或行为,将持续使用行为定义为二元变量,未对持续使用行为细分,忽略了对用户活跃行为的研究。此外,社交网络中用户活跃行为之间有着不可忽视的相互影响,而受制于用户的关系网络数据难以获取,少有研究从该角度对社交网络中的用户行为进行研究。将持续使用行为进一步细分为个体活跃和沉默行为,从网络外部性视角探讨同伴活跃行为对焦点个体活跃行为的影响以及个体网络规模与活跃行为的关系,并进一步探讨个体间关系强度和个体特征的调节作用。以超过百万用户的真实关系网络、个体特征信息和使用行为数据进行实证分析,通过Tobit模型验证上述关系。研究结果表明,同伴活跃度和个体网络规模对个体活跃度有显著的正向作用,同时关系强度具有正向调节作用;个体特征在同伴活跃度与个体活跃度之间起调节作用,具体来说,女性用户和年轻用户受同伴活跃行为的影响更强。从网络外部性的角度探讨用户活跃行为的影响因素,拓展了关于在线社交网络用户持续使用行为的研究和网络外部性测量方式,关注不同节点对于网络外部性贡献的差异性,对今后网络外部性的研究有一定的借鉴意义。基于中国数百万真实用户的数据集,结果更具普适性,同时反映出中国在线社交网络中用户的行为特征,可为今后的研究者提供参考。研究结果可以帮助社交网络平台的管理者更加了解用户活跃度的影响机理以及用户行为之间的内在联系,从而能以更科学合理的方式激发用户活跃度,保持社交网络平台的持续运营。
[Abstract]:The user is the cornerstone of the social network platform. The active behavior of the user creates the content and brings value to the platform, so the user activity is always the focus of the social network platform. Previous studies have only focused on whether the user has the intention or behavior of continuous use, which is defined as a binary variable, without subdividing the behavior of persistent use, and neglecting the study of the active behavior of the user. In addition, the interaction between user's active behavior in social network is not negligible, but it is difficult to obtain the data from the user's relational network, so there is little research on the user's behavior in social network from this point of view. The persistent use behavior is further subdivided into individual active and silent behavior. The influence of peer active behavior on individual active behavior and the relationship between individual network size and active behavior are discussed from the perspective of network externality. Furthermore, the relationship between individuals and the regulation of individual characteristics are discussed. Based on the real relationship network of more than one million users, individual characteristic information and using behavior data, the above relationships are verified by Tobit model. The results show that peer activity and individual network scale have significant positive effects on individual activity, and the relationship intensity has positive regulation effect. Individual characteristics play a regulating role between peer activity and individual activity, specifically, female users and young users are more affected by peer activity. From the perspective of network externality, this paper discusses the influencing factors of users' active behavior, expands the research on the continuous use behavior of online social network users and the measurement of network externality, and pays close attention to the difference of the contribution of different nodes to network externality. It has certain reference significance to the future study of network externality. Based on the data sets of millions of real users in China, the results are more universal and reflect the behavior characteristics of Chinese online social networks, which can be used as a reference for future researchers. The results can help social network platform managers to better understand the influence mechanism of user activity and the internal relationship between user behavior, and thus stimulate user activity in a more scientific and reasonable way. Maintain the continuous operation of the social networking platform.
【作者单位】：西安交通大学管理学院;
【基金】：国家自然科学基金(71301128,91546119,71331005)~~
【分类号】：C912.3;F274

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