Abstract:As propelled by the rapid growth of text data, it is urgent to utilize automated tools to monitor the user relationship, topic trend and the implying values of the platforms. A new modeling framework based on LDA is proposed to evaluate the social networks automatically. The authors first map the text into topic space, eliminating the uncorrelated information based on topic distribution and user feature, then create an evaluation method from social network analysis perspective, mining the structure of the social network from three aspects including user centrality, topic popularity and community activity. Experiments show that promising results are achieved by the new model.
王嘉琦, 徐朝军, 李艺. 基于LDA模型的社交网站自动量化评价研究[J]. 现代图书情报技术, 2013, 29(3): 58-64.
Wang Jiaqi, Xu Chaojun, Li Yi. Quantified Evaluation for Social Networks Based on LDA Model. New Technology of Library and Information Service, 2013, 29(3): 58-64.
[1] Kent State University.Website Evaluation Form[EB/OL].[2012-12-20]. http://www.library.kent.edu/internet/evalform.html. [2] University of Michigan Law School. The Argus Clearinghouse[EB/OL].[2012-12-20]. http://www.clearinghouse.net. [3] Jupiter Research Corporation[EB/OL].[2012-12-10]. http://www.jupiterresearch.com. [4] 李长玲,王效岳,付鑫金.网站定量评价指标体系的构建与权值分配[J]. 图书情报工作 ,2008,52(7): 52-56.(Li Changling, Wang Xiaoyue, Fu xinjin. Construction of Quantitative Evaluation Index System and Weight Assignment for Websites[J].Library and Information Service, 2008,52(7):52-56.) [5] 张圣亮,杨俊,刘彦初.虚拟社区之BBS服务质量实证研究[J]. 世界标准化与质量管理 ,2007(2): 24-29.(Zhang Shengliang, Yang Jun, Liu Yanchu. An Empirical Research on the BBS Service Quality of Virtual Community[J]. World Standardization & Quality Management,2007(2):24-29.) [6] 王蕾, 房俊民. 网络论坛质量评价的影响因素研究[J]. 情报科学 , 2011,29(11): 1647-1652.(Wang Lei, Fang Junmin. Research on Influence Factors of Online Community Evaluation[J]. Information Science, 2011,29(11):1647-1652.) [7] Blei D M, Ng A Y, Jordan M I.Latent Dirichlet Allocation[J].Journal of Machine Learning Research, 2003,3:993-1022. [8] Blei D M. Probabilistic Topic Models[J].Communications of the ACM, 2012,55(4):77-84. [9] Wei X,Croft W B. LDA-based Document Models for Ad-hoc Retrieval[C].In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.2006:178-185. [10] 刁宇峰,杨亮,林鸿飞.基于LDA模型的博客垃圾评论发现[J]. 中文信息学报 , 2011,25(1):41-47.(Diao Yufeng, Yang Liang, Lin Hongfei. LDA-based Opinion Spam Discovering[J].Journal of Chinese Information Processing,2011,25(1):41-47.) [11] 韩晓晖,马军,邵海敏,等.一种基于LDA的Web论坛低质量回帖检测方法[J]. 计算机研究与发展 ,2012,49(9):1937-1946.(Han Xiaohui, Ma Jun, Shao Haimin, et al. An LDA Based Approach to Detect the Low-Quality Reply Posts in Web Forums[J].Journal of Computer Research and Development, 2012,49(9):1937-1946.) [12] Heinrich G. Parameter Estimation for Text Analysis[R].2005. [13] Peters G W, Sisson S A. Bayesian Inference, Monte Carlo Sampling and Operational Risk[J]. Journal of Operational Risk, 2006(2):69-104. [14] Kullback S. Information Theory and Statistics[M].New York: John Wiley and Sons,1959. [15] 王满,徐朝军.网络课程资源自动量化评价研究[J]. 现代图书情报技术 , 2010(1):88-93.(Wang Man, Xu Chaojun. Study on Automatic Quantitative Evaluation of Web Course Resources[J].New Technology of Library and Information Service,2010(1):88-93.)