Twitter trending topics meaning disambiguation

Soyeon Caren Han, Hyunsuk Chung, Do Hyeong Kim, Sungyoung Lee, Byeong Ho Kang

Research output: Chapter in Book/Conference paperConference paperpeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationKnowledge Management and Acquisition for Smart Systems and Services - 13th Pacific Rim Knowledge Acquisition Workshop, PKAW 2014, Proceedings
EditorsYang Sok Kim, Byeong Ho Kang, Deborah Richards
PublisherSpringer-Verlag Italia Srl
Pages126-137
Number of pages12
ISBN (Electronic)9783319133317
DOIs
Publication statusPublished - 2014
Externally publishedYes
EventKnowledge Management and Acquisition for Smart Systems and Services 2014 - Gold Coast, Australia
Duration: 1 Dec 20142 Dec 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8863
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceKnowledge Management and Acquisition for Smart Systems and Services 2014
Abbreviated titlePKAW 2014
Country/TerritoryAustralia
CityGold Coast
Period1/12/142/12/14

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