Topic and user based refinement for competitive perspective identification

Junjie Lin, Wenji Mao, Dajun Zeng

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

1 Scopus citations

Abstract

The competitive perspective implied in online texts reflect people's conflicts in their stances and viewpoints. Competitive perspective identification aims to determine people's inclinations to one of multiple competitive perspectives, which is an important research issue and can facilitate many security-related applications. As the word usage of different perspectives is distinct in various topics, in this paper, we first proposes a supervised topic-refined method for competitive perspective identification. Our method refines perspective classifiers with the document-Topic distributions mined from texts. To reduce human labor in data annotation, we further extend our work in a semi-supervised manner and propose a user-based bootstrapping framework. As the perspectives people hold are relatively stable, our bootstrapping process leverages the user-level perspective consistency to select high-quality classified texts from unlabeled corpus and boost the perspective classifier iteratively. Experimental studies show the effectiveness of our proposed approach in identifying the competitive perspectives of online texts.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Intelligence and Security Informatics
Subtitle of host publicationSecurity and Big Data, ISI 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages131-133
Number of pages3
ISBN (Electronic)9781509067275
DOIs
StatePublished - Aug 8 2017
Externally publishedYes
Event15th IEEE International Conference on Intelligence and Security Informatics, ISI 2017 - Beijing, China
Duration: Jul 22 2017Jul 24 2017

Other

Other15th IEEE International Conference on Intelligence and Security Informatics, ISI 2017
CountryChina
CityBeijing
Period7/22/177/24/17

Keywords

  • Competitive perspective identification
  • Topic-based refinement
  • User-based bootstrapping

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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