期刊论文

Creating Dynamic Tags for Social Networking Groups

中文

数据分析与知识发现

2096-3467

2019

3

10

98-109

10.11925/infotech.2096-3467.2018.1108

国家社会科学基金一般项目(16BTQ076)

本校为第一机构

【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...

[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 characteris...