Solving the Difficult Problem of Topic Extraction in Thai Tweets

Authors

  • Rungsiman Nararatwong The Graduate University for Advanced Studies, Kanagawa, Japan. National Institute of Informatics, Tokyo, Japan
  • Roberto Legaspi Research Organization of Information and Systems, Transdisciplinary Research Integration Center, The Institute of Statistical Mathematics, Tokyo, Japan
  • Nagul Cooharojananone Chulalongkorn University
  • Hitoshi Okada National Institute of Informatics, Tokyo, Japan
  • Hiroshi Maruyama Research Organization of Information and Systems, Transdisciplinary Research Integration Center, The Institute of Statistical Mathematics, Tokyo, Japan

Keywords:

LDA, Topic Extraction, Thai Tweets,

Abstract

We tackled in this study the difficult problem of topic extraction in Thai tweets on the country’s historic flood in 2011. After using Latent Dirichlet Allocation (LDA) to extract the topics, the first difficulty that faced us was the inaccuracy the word segmentation task that affected our interpretation of the LDA result. To solve this, we refined the stop word list from the LDA result by removing uninformative words caused by the word segmentation, which resulted to a more relevant and comprehensible outcome. With the improved results, we then constructed a rule-based categorization model and used it to categorize all the collected tweets on a per-week scale to observe changes in tweeting trend. Not only did the categories reveal the most relevant and compelling topics that people raised at that time, they also allowed us to understand how people perceived the situations as they unfold over time

Downloads

Published

2016-09-01

How to Cite

Nararatwong, R., Legaspi, R., Cooharojananone, N., Okada, H., & Maruyama, H. (2016). Solving the Difficult Problem of Topic Extraction in Thai Tweets. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(6), 141–145. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1263

Issue

Vol. 8 No. 6: Emerging Technologies in Communication and Computer Engineering for Smart City Applications II

Section

Articles

License

TRANSFER OF COPYRIGHT AGREEMENT

The manuscript is herewith submitted for publication in the Journal of Telecommunication, Electronic and Computer Engineering (JTEC). It has not been published before, and it is not under consideration for publication in any other journals. It contains no material that is scandalous, obscene, libelous or otherwise contrary to law. When the manuscript is accepted for publication, I, as the author, hereby agree to transfer to JTEC, all rights including those pertaining to electronic forms and transmissions, under existing copyright laws, except for the following, which the author(s) specifically retain(s):

  1. All proprietary right other than copyright, such as patent rights
  2. The right to make further copies of all or part of the published article for my use in classroom teaching
  3. The right to reuse all or part of this manuscript in a compilation of my own works or in a textbook of which I am the author; and
  4. The right to make copies of the published work for internal distribution within the institution that employs me

I agree that copies made under these circumstances will continue to carry the copyright notice that appears in the original published work. I agree to inform my co-authors, if any, of the above terms. I certify that I have obtained written permission for the use of text, tables, and/or illustrations from any copyrighted source(s), and I agree to supply such written permission(s) to JTEC upon request.