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Trending sentiment-topic detection on twitter

  • Baolin Peng
  • , Jing Li
  • , Junwen Chen
  • , Xu Han
  • , Ruifeng Xu
  • , Kam Fai Wong
  • Chinese University of Hong Kong
  • Peking University
  • Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Twitter plays a significant role in information diffusion and has evolved to an important information resource as well as news feed. People wonder and care about what is happening on Twitter and what news it is bringing to us every moment. However, with huge amount of data, it is impossible to tell what topic is trending on time manually, which makes real-time topic detection attractive and significant. Furthermore, Twitter provides a platform of opinion sharing and sentiment expression for events, news, products etc. Users intend to tell what they are really thinking about on Twitter thusmakes Twitter a valuable source of opinions. Nevertheless, most works about trending topic detection fail to take sentiment into consideration. This work is based on a non-parametric supervised real-time trending topic detectionmodelwith sentimental feature.Experiment shows our model successfully detects trending sentimental topic in the shortest time. After a combination of multiple features, e.g. tweet volume and user volume, it demonstrates impressive effectiveness with 82.3% recall and surpasses all the competitors.

Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 16th International Conference, CICLing 2015, Proceedings
EditorsAlexander Gelbukh
PublisherSpringer Verlag
Pages66-77
Number of pages12
ISBN (Print)9783319181165
DOIs
StatePublished - 2015
Externally publishedYes
Event16th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2015 - Cairo, Egypt
Duration: 14 Apr 201520 Apr 2015

Publication series

NameLecture Notes in Computer Science
Volume9042 9042 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2015
Country/TerritoryEgypt
CityCairo
Period14/04/1520/04/15

Keywords

  • Online social network
  • Sentiment analysis
  • Trending topic detection
  • Twitter

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