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THAI TOPIC DETECTION IN TWITTER

JuthathipJuengjaroennorasuk5088172ITCS/B
RatchataLimnumkum5088230ITCS/B
RaviThongpan5088286ITCS/B

B.Sc.(INFORMATION AND COMMUNICATION TECHNOLOGY)

Project Advisor: Dr.Ananta Srisuphab

Abstract

Nowadays, social networks are widely used and Twitter is one of the most popular. As Twitter is a micro-blogging, users can post short text messages, called tweets, which allow the users to follow and view each others tweets. This will cause a ton of tweets to be seen by the users. Therefore, it is necessary to have a Twitter client that can organize this high number of tweets. This research project describes the design and development of a mobile and web application named Thai Topic Detection in Twitter (TTD) targeted at Twitter’s users. The TTD provides a personal tweets classification system that helps Twitter’s users to easily view the tweets in which they are interested, and in which the system has already been organized into five topics: IT, Economics, Sports, Entertainment, and Politics. The TTD works with an OpenNLP, and WordNet to detect the meaningful words from a sentence and extract the features respectively. In addition, the TTD will classify the topic by using a Locality Sensitive Hashing (LSH) algorithm. The TTD runs on mobile phones and web browsers, which allows the users to access the TTD from anywhere at any time.

 

KEYWORDS: MICRO-BLOGGING / TWEET / OPENNLP / WORDNET / LSH / TOPIC DETECTION

 

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