基于粒子群的微博用户影响力评价算法研究  

The Calculate Algorithm Study for Microblog User Influence Based on Particle Swarm Optimization

作　　者：江玲[1] 夏婷婷[1] 蒋艺[1] 范琳 

机构地区：[1]武夷学院数学与计算机学院,福建武夷山354300 [2]绵阳天眼激光科技有限公司,四川绵阳621000

出　　处：《武夷学院学报》2017年第6期63-67,共5页Journal of Wuyi University

基　　金：武夷学院校科研基金资助项目(XL201708)

摘　　要：针对群体智能与微博社交网络用户行为之间的相似性,对基于粒子群的微博用户影响力的评价算法展开研究。对微博用户数据进行必要的预处理,旨在消除冗余数据和无功数据对影响力评价的消极影响。介绍了适应微博社交网络背景的粒子群算法的速度和位移更新公式。完成微博社交网络中用户相互影响力的评价,该评价算法将微博社交网络中用户群体表现出的自组织性和纳入评价体系中,在消除少量数据引起的评价偏差方面取得一定成效。According to the fact that the user＇s behaviors of microblog social network match the five principles of Swarm intelligence, a novel algorithm based on particle swarm optimazation is studyed in this paper to calculate the influence bewteen microblog users. First, in order to avoid the negative effect from redundant and useless microblog data, data preprocessing is necessary. Second, the variable is defined as the velocity hange in the proposed algorithm. Finally, the process to calculate the influence between users is introduced. The experiment results show that the novel algorithm is effective in avoiding the negative influence from signal index.

关 键 词：粒子群算法 微博社交网络 用户相互影响力 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]