Latent Community Topic Analysis: Integration of Community Discovery with Topic Modeling

Download Now
Provided by: Association for Computing Machinery
Topic: Big Data
Format: PDF
In this paper, the authors study the problem of latent community topic analysis in text-associated graphs. With the development of social media, a lot of user-generated content is available with user networks. Along with rich information in networks, user graphs can be extended with text information associated with nodes. Topic modeling is a classic problem in text mining and it is interesting to discover the latent topics in text-associated graphs. Different from traditional topic modeling methods considering links, they incorporate community discovery into topic analysis in text-associated graphs to guarantee the topical coherence in the communities so that users in the same community are closely linked to each other and share common latent topics.
Download Now

Find By Topic