Clustering users in micro blogging social networks using probabilistic topic modeling - A framework

Hossein Dolatabadi, Lay Ki Soon, Mahdi Negahi Shirazi, Mohammad Mohammadi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)


Social network is a term used to represent a large group of activities using the web and mobile technologies. The micro blogging social networks provide an appropriate ground for the users to explain themselves and express their ideas as well as interacting with the others. The growth of the social networks' users creates the necessity of extracting and analyzing the contents of the users' notes and multimedia products. In this paper, a new methodology is defined to characterize users based on the contents of their posts in micro blogging social networks and also to create clusters of users by means of highlighting the distribution of words representing a topic in the contents of micro blogging social networks.

Original languageEnglish
Title of host publicationProceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012
Number of pages4
Publication statusPublished - 2012
Externally publishedYes
EventInternational Conference on Computational Science and Applications 2012
- Salvador Bahia, Brazil
Duration: 18 Jun 201221 Jun 2012 (Proceedings)


ConferenceInternational Conference on Computational Science and Applications 2012
Abbreviated titleICCSA 2012
CitySalvador Bahia
Internet address


  • Latent Dirichlet Allocation (LDA)
  • Micro blogging
  • Social network
  • Topic modeling algorithm
  • User clustering

Cite this