中国科学技术大学学报 ›› 2018, Vol. 48 ›› Issue (9): 730-738.DOI: 10.3969/j.issn.0253-2778.2018.09.007

• 论著 • 上一篇    下一篇

多关系社交网络中基于兴趣匹配的网络舆情传播模型

孙更新,宾晟   

  1. 青岛大学数据科学与软件工程学院,青岛 266071
  • 收稿日期:2018-05-24 修回日期:2018-09-18 接受日期:2018-09-18 出版日期:2018-09-30 发布日期:2018-09-18
  • 通讯作者: 孙更新
  • 作者简介:孙更新(通讯作者), 男, 1978年生, 博士/副教授. 研究方向: 数据挖掘、复杂网络. E-mail: sungengxin@qdu.edu.cn
  • 基金资助:
    教育部人文社会科学研究青年项目(15YJC860001);青岛市社会科学规划项目(QDSKL1701074);山东省自然基金面上项目(ZR2017MG011);山东省社会科学规划项目(17CHLJ16)资助.

Network public opinion propagation model based on interest matching in multiple relationship social network

SUN Gengxin, BIN Sheng   

  1. College of Data Science and Software Engineering, Qingdao University, Qingdao 266071
  • Received:2018-05-24 Revised:2018-09-18 Accepted:2018-09-18 Online:2018-09-30 Published:2018-09-18

摘要: 以网络爬虫方式获取新浪微博用户属性信息及微博内容数据,利用数据挖掘技术从中发现微博用户间的多种显式和隐式关系.在此基础上,提出一种基于半监督学习的用户兴趣匹配预测算法,参照仓室模型的传播个体状态划分方法,基于传播个体间的兴趣匹配度界定各状态之间的转移过程和转移概率,进而构建基于用户兴趣匹配的网络舆情传播模型.研究结果表明,该模型能够较好地描述社交网络中的舆情传播规律,重现网络舆情在社交网络中的真实传播过程链.

关键词: 舆情传播, 传播模型, 复杂网络, 数据挖掘, 社交网络

Abstract: The relationship between user profiles and the data of microblog content in Sina microblog was obtained by programming and web crawler, and a variety of explicit or implicit relationships between microblog users were discovered by using data mining. On the basis of this, a semi-supervised user interest matching prediction algorithm was proposed. According to the individual state division method of compartment model, a network public opinion propagation model is constructed based on user interest matching through state transition analysis and inference of state transition probability. The results show that the model can well describe the laws of public opinion propagation in social networks, and reproduce the real propagation process of network public opinion in the social network from the perspective of complex networks.

Key words: public opinion propagation, propagation model, complex network, data mining, social networks

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