Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
4-2014
Abstract
In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also demonstrate that CBS model perform as well as other state-of-the-art models in modeling topics, but outperforms the rest in mining user communities
Discipline
Computer Sciences | Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Publication
Proceedings of the 2014 SIAM International Conference on Data Mining: April 24-26, Philadelphia, PA
First Page
479
Last Page
487
ISBN
9781611973440
Identifier
10.1137/1.9781611973440.55
Publisher
SIAM
City or Country
Philadephia, PA
Citation
HOANG, Tuan Anh; COHEN, William; and LIM, Ee Peng.
On modeling community behaviors and sentiments in microblogging. (2014). Proceedings of the 2014 SIAM International Conference on Data Mining: April 24-26, Philadelphia, PA. 479-487.
Available at: https://ink.library.smu.edu.sg/sis_research/1976
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1137/1.9781611973440.55
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Social Media Commons