帮助 关于我们

返回检索结果

SNS中影响力用户预测研究——基于不平衡数据的多种数据挖掘方法对比
PREDICTING INFLUENTIAL USERS IN SNS: THE COMPARISON OF DATA MINING METHODS BASED ON IMBALANCED DATA

查看参考文献39篇

柴雯 1   左美云 2   许伟 3 *   王轶博 4  
文摘 识别和预测SNS中某一话题中有影响力的用户,对于营销战略的精准实施和营销成本的节约具有重要意义.已有相关研究大都聚焦于静态情境下的用户影响力识别,而对于用户影响力预测问题的探讨还非常少.因此,本研究提出了一个综合的预测研究框架,结合不同的预测指标选取策略、属性选择方法和数据采样处理流程,并应用多种分类预测算法,对微博平台的用户影响力进行了实证分析.通过多种预测效果评价指标进行验证,表明本文提出的方法在用户影响力预测上具有较高的精度,显著提高了在个人层面的预测效果,在用户影响力预测方面具有较好的应用价值.
其他语种文摘 Identifying and predicting influential users in SNS under a certain topic is very important issue for marketing strategy implement and cost saving. The identification has been greatly focused on static context in available literatures, but the prediction is rarely researched. Hence, a synthesized prediction research framework is proposed in this paper to analyze the users’ influence in SNS, in which different indicators’ datasets, different feature selection methods, different proportions of data oversampling and multiple prediction algorithms are included. Our empirical result, which is validated by different performance evaluation indicators, shows that the proposed method is of high precision in predicting users’ influence in SNS, and the prediction ccuracy at individual level has been significatly improved. Therefore, the proposed method is good for practical application in predicting users’ influence in SNS.
来源 系统科学与数学 ,2015,35(9):1059-1072 【核心库】
关键词 SNS ; 用户影响力 ; 预测 ; 数据挖掘 ; 不平衡数据
地址

1. 中国人民大学商学院, 数据工程与知识工程教育部重点实验室, 北京, 100872  

2. 中国人民大学, 数据工程与知识工程教育部重点实验室, 北京, 100872  

3. 中国人民大学信息学院, 北京, 100872  

4. 中国人民大学信息学院, 数据工程与知识工程教育部重点实验室, 北京, 100872

语种 中文
文献类型 研究性论文
ISSN 1000-0577
学科 自动化技术、计算机技术
基金 中国人民大学中央高校基本科研业务费专项 ;  国家自然科学基金 ;  国家社会科学基金重大项目 ;  国家教育部人文社会科学研究项目 ;  北京市社会科学基金 ;  北京市科技新星计划项目
文献收藏号 CSCD:5540459

参考文献 共 39 共2页

1.  Amblee N. Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International Journal of Electronic Commerce,2011,16(2):91-114 被引 4 次    
2.  Cheung M Y. Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce,2009,13(4):9-38 被引 6 次    
3.  Culnan M J. How large U.S. companies can use Twitter and other social media to gain business value. MIS Quarterly Executive,2010,9(4):243-259 被引 3 次    
4.  Stephen A T. Driving value from social commerce networks. Journal of Marketing Research,2010,47(2):215-228 被引 4 次    
5.  O'Keefe D J. Persuasion: Theory and Research. 2nd Edition,2002 被引 1 次    
6.  Huffaker D. Dimensions of leadership and social influence in online communities. Human Communication Research,2010,36(4):593-617 被引 3 次    
7.  Li F. Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs. Decision Support Systems,2011,51(1):190-197 被引 15 次    
8.  Heidemann J. Identifying key users in online social networks: A PageRank based approach. Proceedings of the 31th International Conference on Information Systems,2010:79 被引 1 次    
9.  Song X. Identifying opinion leaders in the blogosphere. Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management,2007:6-8 被引 1 次    
10.  Agarwal R. Editorial overview - The interplay between digital and social networks. Information Systems Research,2008,19(3):243-252 被引 1 次    
11.  Wu S. Who says what to whom on Twitter. Proceedings of the 20th International Conference on World Wide Web,2011:705-714 被引 10 次    
12.  Bakshy E. Everyone's an influential: Quantifying influence on Twitter. Proceedings of the 4th ACM International Conference on Web Search and Data Mining,2011:65-74 被引 12 次    
13.  Chai W. ACQR: A novel framework to identify and predict influential users in Micro-Blogging. Proceedings of 17th Pacific Asia Conference on Information Systems,2013:20 被引 1 次    
14.  Katz E. Personal Influence: The Part of Played by People in the Flow of Mass Communications,1955 被引 1 次    
15.  Rogers E M. The Diffusion of Innovation. 4th Edition,1995 被引 1 次    
16.  Freeman L C. Centrality in social networks: Conceptual clarification. Social Networks,1979,1(3):215-239 被引 431 次    
17.  Newman M E. The structure and function of complex networks. Society for Industrial and Applied Mathematics Review,2003,45(2):167-256 被引 971 次    
18.  Bonacich P. Some unique properties of eigenvector centrality. Social Networks,2007,29(4):555-564 被引 36 次    
19.  Katz L. A new status index derived from sociometric analysis. Psychometrika,1953,18(1):39-43 被引 152 次    
20.  Page L. The PageRank citation ranking: Bringing order to the web. Stanford Digital Libraries Working Paper,1998 被引 13 次    
引证文献 0 篇
论文科学数据集
PlumX Metrics
相关文献

 作者相关
 关键词相关
 参考文献相关

版权所有 ©2008 中国科学院文献情报中心 制作维护：中国科学院文献情报中心
地址：北京中关村北四环西路33号 邮政编码：100190 联系电话：(010)82627496 E-mail:cscd@mail.las.ac.cn 京ICP备05002861号-4 | 京公网安备11010802043238号