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Twitter trending topics meaning disambiguation


Han, SC and Chung, H and Kim, DH and Lee, S and Kang, BH, Twitter trending topics meaning disambiguation, Lecture Notes in Artificial Intelligence 8863: Proceedings of the 13th Pacific Rim Knowledge Acquisition Workshop (PKAW2014), 1-2 December 2014, Gold Coast, Australia, pp. 126-137. ISSN 0302-9743 (2014) [Refereed Conference Paper]

Copyright Statement

Copyright 2014 Springer International Publishing Switzerland

DOI: doi:10.1007/978-3-319-13332-4_11


Twitter is one of the most popular social media services that allow users to share and spread information. Twitter monitors their users’ postings and detects the most discussed topics of the moment. Then, they publish these topics on the list, called ‘Trending Topics’. Trending Topics on Twitter shows the list of top 10 trending topics but each topic consists of short phrase or keyword, which does not contain any explanation of those meanings. It is almost impossible to identify what a trending topic is about unless you read all related tweets. The goal of this paper is finding the most successful method that uses to retrieve the representative contents of trending topics in order to disambiguate the meaning of topics. We first collected the trending topics and tweets related to them. Then, we applied four types of information retrieval approaches (key factor extraction, named entity recognition, topic modelling, and automatic summarization) for extracting the representative contents of trending topics. We conducted human experiments with 20 postgraduate students.

Item Details

Item Type:Refereed Conference Paper
Keywords:Twitter, Twitter trending topics, social media, disambiguation
Research Division:Information and Computing Sciences
Research Group:Information systems
Research Field:Information systems not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Information services
Objective Field:Information services not elsewhere classified
UTAS Author:Han, SC (Ms Caren Han)
UTAS Author:Chung, H (Mr David Chung)
UTAS Author:Kang, BH (Professor Byeong Kang)
ID Code:98396
Year Published:2014
Deposited By:Information and Communication Technology
Deposited On:2015-02-13
Last Modified:2018-01-16

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