计算机应用 ›› 2017, Vol. 37 ›› Issue (3): 654-659.DOI: 10.11772/j.issn.1001-9081.2017.03.654

• 第四届大数据学术会议(CCF BIGDATA2016) • 上一篇    下一篇

基于关联关系的微博用户可信度分析方法

李付民1, 佟玲玲2, 杜翠兰2, 李扬曦2, 张仰森1   

  1. 1. 北京信息科技大学 智能信息处理研究所, 北京 100192;
    2. 国家计算机网络应急技术处理协调中心, 北京 100190
  • 收稿日期:2016-09-30 修回日期:2016-10-20 出版日期:2017-03-10 发布日期:2017-03-22
  • 通讯作者: 佟玲玲
  • 作者简介:李付民(1990-),男,河南商丘人,硕士研究生,CCF会员,主要研究方向:中文信息处理、数据挖掘;佟玲玲(1984-),女,辽宁阜新人,高级工程师,博士,主要研究方向:多媒体内容分析与编码、自然语言处理;杜翠兰(1966-),女,湖北武汉人,主要研究方向:网络信息安全、自然语言处理;李扬曦(1982-),男,甘肃兰州人,高级工程师,博士研究生,主要研究方向:机器学习、数据挖掘;张仰森(1962-),男,山西临猗人,教授,博士,CCF高级会员,主要研究方向:中文信息处理、人工智能、Web内容安全。
  • 基金资助:
    国家自然科学基金资助项目(61370139);北京市属高等学校创新团队建设与教师职业发展计划项目(IDHT20130519)。

Weibo users credibility evaluation based on user relationships

LI Fumin1, TONG Lingling2, DU Cuilan2, LI Yangxi2, ZHANG Yangsen1   

  1. 1. Institute of Intelligence Information Processing, Beijing Information Science and Technology University, Beijing 100192, China;
    2. National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100190, China
  • Received:2016-09-30 Revised:2016-10-20 Online:2017-03-10 Published:2017-03-22
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61370139), the Project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges Under Beijing Municipality (IDHT20130519).

摘要: 随着微博研究的深入,对微博用户可信度的评价成为一个研究热点。针对微博用户可信度评价的问题,提出了一种基于关联关系的用户可信度分析方法。以新浪微博为研究对象,首先从用户的资料信息、交互信息和行为信息三个方面出发,分析了用户的7个相关特征,利用层次分析法(AHP),进而得到用户自评价可信度;然后以用户自评价作为基点,以用户关系网络作为载体,结合用户之间潜在的用户互评关系,通过改进PageRank算法,提出了用户可信度评价模型User-Rank,进而,利用关系网络中其他用户对待分析用户的可信度进行综合评价。大规模的微博真实数据的实验表明,所提方法能够取得良好的用户可信度评价效果。

关键词: 用户自评价, 关系网络, 用户可信度, 用户关联关系, 层次分析法, PageRank

Abstract: With the deepening of Weibo research, credibility evaluation of Weibo users has become a research hotspot. Aiming at the problem of Weibo users' credibility evaluation, a user confidence analysis method based on association was proposed. Taking Sina Weibo as the research object, firstly, seven characteristics of the user from three aspects: user information, interactive information and behavior information were analyzed, and the user self-evaluation credibility was got by using Analytic Hierarchy Process (AHP). Then, by using the user self-evaluation as the base point, the user relationship network as the carrier, and the potential users' evaluation relationship among the users, was improved the PageRank algorithm, and the user credibility evaluation model called User-Rank was proposed. The proposed model was used to evaluate comprehensively credibility of users by other users in relational network. Experiments on large scale Weibo real data show that the proposed method can obtain good evaluation results of user credibility.

Key words: user self-evaluation, relationship network, user credibility, user relationships, Analytic Hierarchy Process (AHP), PageRank

中图分类号: