基于多关系与属性的主题层次影响力评估算法

Topical influence evaluation algorithm based on multi-relationship and personal attributes

为准确分析和度量微博用户在主题层次的影响力,提出一种综合考虑用户多关系与个人属性的影响力评估算法。该算法以主题为单位,对用户交互行为进行分析,构建了包含转发关系、评论关系、复制关系和提及关系的多关系网络,并给出转移概率计算模型;从用户活跃度、用户权威度、博文质量、粉丝质量4个角度考虑,构建了基于主题的用户个人属性影响力指标体系,并使用层次分析法给出各指标的权重;基于PageRank算法思想,提出了融合用户关系与属性特征的影响力计算方法。通过新浪微博数据集的对比实验,证明了算法的准确性和有效性。

To accurately analyze and measure the topical influence of micro blog users, a new influence evaluation algorithm based on multi-relationship and personal attributes is presented. Taking topic as unit, the multi-relational influence network including repost, comment, copy and mention relations is constructed by analyzing user interaction behavior, and the transi- tion probability calculation model is given. In consideration of user activity, user authority, micro-blog quality and follower quality, an index system of user＇s personal attributes influence based on the topic is constructed, and the weight of each in- dicator is given by using the method of analytic hierarchy process （AHP）. Finally, a calculation method of influence based on PageRank is designed by fusing user relations and attributes. A large number of experiments according to real data sets show that the proposed method is accurate and effective.