Learning Text Patterns to Detect Opinion Targets

Filipa Peleja, João Magalhães

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

2 Citations (Scopus)

Abstract

Exploiting sentiment relations to capture opinion targets has recently caught the interest of many researchers. In many cases target entities are themselves part of the sentiment lexicon creating a loop from which it is difficult to infer the overall sentiment to the target entities. In the present work we propose to detect opinion targets by extracting syntactic patterns from short-texts. Experiments show that our method was able to successfully extract 1,879 opinion targets from a total of 2,052 opinion targets. Furthermore, the proposed method obtains comparable results to SemEval 2015 opinion target models in which we observed the syntactic structure relation that exists between sentiment words and their target.
Original languageEnglish
Title of host publicationKDIR 2015 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, part of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015), Volume 1, Lisbon, Portugal, November 12-14, 2015
Pages337-343
Number of pages7
DOIs
Publication statusPublished - 2015
Event7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015 - Lisbon, Portugal
Duration: 12 Nov 201514 Nov 2015

Conference

Conference7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015
CountryPortugal
CityLisbon
Period12/11/1514/11/15

Keywords

  • Opinion mining
  • Opinion targets
  • Sentiment analysis

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