Stance Classification by Recognizing Related Events about Targets

Akira Sasaki, Junta Mizuno, Naoaki Okazaki, Kentaro Inui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Recently, many people express their opinions using social networking services such as Twitter and Facebook. Each opinion has a stance related to something such as product, service, and politics. The task of detecting a stance is known as sentiment analysis, reputation mining, and stance detection. A popular approach for stance detection uses sentiment polarity towards a target in a text. This approach is known as targeted sentiment analysis. If a target appears in text, the detecting stance based on targeted sentiment polarity would work well. However, how can we detect stance towards an event? (e.g. 'I cannot understand why man can marry only with a woman', 'The problem of low birth rate becomes more severe' to the event 'Allowing same-sex marriage'). To detect these stances, it is necessary to recognize a situation in which the event occurs or does not occur. To classify texts including these phenomena, we propose a classification method based on machine learning considering PRIOR-SITUATION and EFFECT.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages582-587
Number of pages6
ISBN (Electronic)9781509044702
DOIs
Publication statusPublished - 2017 Jan 12
Event2016 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2016 - Omaha, United States
Duration: 2016 Oct 132016 Oct 16

Publication series

NameProceedings - 2016 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2016

Other

Other2016 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2016
Country/TerritoryUnited States
CityOmaha
Period16/10/1316/10/16

Keywords

  • Natural language processing
  • Sentiment analysis
  • Stance classification

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications

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