摘要
在海量数据背景下,针对社交网站中队成员关系、话题热度及内涵的价值倾向等评价问题,提出一个基于LDA的两阶段社交网站自动量化评价模型。首先通过LDA方法将文本内容映射到主题空间,依据文本所属主题和用户特征来剔除垃圾信息;对于筛选出的信息,从用户、话题和社区三个角度提出一个新的社交网站的量化分析方法。最后,通过对西祠胡同的实验分析验证该模型的有效性和可行性。
As propelled by the rapid growth of text data, it is urgent to utilize automated tools to monitor the user rela- tionship, 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 community activity. Experiments show that promising results three aspects including user centrality, topic popularity and are achieved by the new model.
出处
《现代图书情报技术》
CSSCI
北大核心
2013年第3期58-64,共7页
New Technology of Library and Information Service
基金
全国教育科学"十一五"规划2009年度教育部青年专项课题"网络课程使用现状自动量化评价系统研究"(项目编号:ECA090441)的研究成果之一
