Conference Proceeding Article
Twitter is a popular online social information network service which allows people to read and post messages up to 140 characters, known as “tweets”. In this paper, we focus on the tweets between pairs of individuals, i.e., the tweet replies, and propose a generative model to discover topics among groups of twitter users. Our model has then been evaluated with a tweet dataset to show its effectiveness.
Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Data Management and Analytics
Proceedings of the 10th Workshop on Mining and Learning with Graphs (MLG-2012), Edinburgh
Katholieke Universiteit Leuven
City or Country
DAI, Bingtian; LIM, Ee Peng; and PRASETYO, Philips Kokoh.
Topic Discovery from Tweet Replies. (2012). Proceedings of the 10th Workshop on Mining and Learning with Graphs (MLG-2012), Edinburgh. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3160
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.