摘要
【目的】利用网络社群话题及成员兴趣标签网络为社群动态生成能够表征其特点及短期关注兴趣的社群标签。【方法】利用BTM模型挖掘社群话题短文本的主题,并根据社群成员兴趣标签网络的特征,挖掘社群成员关注兴趣点,综合两者结果生成社群动态标签。以“豆瓣小组”为例对模型进行实证。【结果】基于话题社群标签与社群特征具有强关联性、稳定性强,基于成员兴趣网络标签能够及时准确表征社群动态兴趣。【局限】样本数据集不能涵盖所有类型的网络社群,仅从两类社群验证了模型的准确性与有效性。【结论】基于社群话题及成员兴趣的社群标签动态生成模型能够准确挖掘出社群特点及成员短期关注点,提高社群定义的及时性与准确性,解决用户信息获取、网络社群选择的困难。
[Objective]This paper proposes a method to generate dynamic labels for the characteristics of online communities and their short-term interest.[Methods]Firstly,we used the BTM model to extract the discussion topics from short texts posted by online community members.Then,we explored their actual interest based on personal labels.Finally,we combined these results to create dynamic tags for the communities.[Results]We examined the proposed model empirically with data from two types of“Douban groups”.Tags of discussion topics and characteristics of the communities showed strong and stable relevant relationship.The tags for personal interest could accurately represent the community’s dynamic interest.[Limitations]More online communities should be included in future studies.[Conclusions]The proposed model accurately identifies characteristics of online community and its members’short-term concerns,which also benefits information acquisition.
作者
蒋武轩
熊回香
叶佳鑫
安宁
Jiang Wuxuan;Xiong Huixiang;Ye Jiaxin;An Ning(School of Information Management,Central China Normal University,Wuhan 430079,China;School of Information Management,Wuhan University,Wuhan 430079,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2019年第10期98-109,共12页
Data Analysis and Knowledge Discovery
基金
国家社会科学基金一般项目“基于人类动力学的社交网络信息交流行为研究”(项目编号:16BTQ076)的研究成果之一
关键词
社群标签
标签生成
BTM
复杂网络
Community Labels
Tag Generation
BTM
Complex Networks
