【摘要】 伴随着网络技术应运而生的社交网络平台打破了固有的信息传播方式,成为日常生活中重要的信息渠道,信息传播的方式发生了翻天覆地的变化。在社交网络平台中,为用户提供了多种交互功能,用户可以进行多种行为。发布行为产生数据信息,这些基本数据信息是社交网络信息的重要组成部分。用户的转发行为促使该基本数据信息在社交网络中有效传播。对原创贴文的点赞和评论增添了原贴文的信息承载量,可以有效地增强原贴文的影响力。本文从用户行为方式和互动规律的角度出发,系统研究了社交网络中用户行为和贴文特征。基于PCA主成分分析算法,将各组成因素进行相关性研究,得到社交网络节点影响力函数表达式。更多还原

【Abstract】 Along with the network technology arises at the historic moment of social networking platform to break the inherent way of information dissemination,which has become the important channels of information in daily life,great changes have taken place in information dissemination way. In the social network platform,it provides a variety of interactive functions for users,and users can conduct a variety of behaviors. Publishing behavior generates data information,which is an important part of social network information. Users’ forwarding behavior makes this basic data information spread effectively in social networks. Thumb up and comments on original posts increase the information load of original posts,which can effectively enhance the influence of original posts. From the perspective of user behavior pattern and interaction rule,this paper systematically studies user behavior and post text characteristics in social network. Based on PCA principal component analysis algorithm,the correlation of each component factor is studied,and the expression of influence function of social network nodes is obtained.更多还原