电子学报2016，Vol.44Issue(4)：898-905,8.DOI:10.3969/j.issn.0372-2112.2016.04.021
基于多维特征分析的社交网络意见领袖挖掘
Mu lti-Featu re Based Opinion Leader Mining in Social Networks
摘要
Abstract
Mining opinion leaders in social network is important for analysis of information dissemination and evolu-tion of public opinion.This paper conducts the study on this problem considering structural features,behavior and emotional characteristics comprehensively.Firstly,we extract topics from micro-blogging texts,and get user communities according to the topic division,and an interactive network topology of topic community is built with the following relationships.Then, three kinds of user feature are gained from different aspect:network structure,user behavior and user sentiment.Finally,ac-cording to the analysis of users’influence distribution,opinion leaders mining algorithm MFP (Multi-Feature PageRank)is proposed.Experiments show that the algorithm can obtain the potential opinion leader nodes effectively,and have a good performance in support rate from other user nodes.关键词
社交网络/话题/情感分析/意见领袖Key words
social network/topic/sentiment analysis/opinion leader分类
信息技术与安全科学引用本文复制引用
曹玖新,陈高君,吴江林,刘波,周涛,胥帅,朱子青..基于多维特征分析的社交网络意见领袖挖掘[J].电子学报,2016,44(4):898-905,8.基金项目
国家863高技术研究发展计划（No．2013AA013503）；东南大学计算机网络和信息集成教育部重点实验室基金（No．93k-9）；国家973重点基础研究发展计划（No．2010CB328104）；国家自然科学基金（No．61272531，No．61202449，No．61272054，No．61370207，No．61370208，No．61300024，No．61320106007，No．61472081）；高等学校博士点学科专项科研基金（No．2011009213002）；江苏省科技计划基金（No．SBY2014021039－10）；江苏省网络与信息安全重点实验室基金 （）
