Abstract

Emotions in a sentence can hold many roles in the field of sentiment analysis, knowing emotions can also be known through facial expressions, speech and text. In this paper we try to find the best definition for WordNet, by utilizing ANEW and ISEAR datasets. Sentences from WordNet that match the parameters of the two datasets will be searched for emotion, labeled according to the class and selected. This can be used in text mining. The result of this research showed that not all definitions in wordnet can accurately match all datasets and contexts.

Original languageEnglish
Title of host publicationProceedings - 2018 International Seminar on Application for Technology of Information and Communication
Subtitle of host publicationCreative Technology for Human Life, iSemantic 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages249-252
Number of pages4
ISBN (Electronic)9781538674864
DOIs
Publication statusPublished - 27 Nov 2018
Event3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018 - Semarang, Indonesia
Duration: 21 Sept 201822 Sept 2018

Publication series

NameProceedings - 2018 International Seminar on Application for Technology of Information and Communication: Creative Technology for Human Life, iSemantic 2018

Conference

Conference3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018
Country/TerritoryIndonesia
CitySemarang
Period21/09/1822/09/18

Keywords

  • ANEW
  • POS tagging
  • Thayer's Model
  • WordNet
  • word sense disambiguation

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