Abstract

Emotion Detection is a part of Natural Language Processing (NLP) that still evolve. Emotional Corpus that had been widely used are Wordnet Affect Emotion (WNA) and ANEW (Affective Norms for English Words). There are two ways to analyze the text based Emotion Detection: Categorical and Dimensional Model. Each model has different advantages and disadvantages. And each model has a different concept to predict emotion. The contribution of this research is forming automatic emotional corpus with merging two computational model. It called Corpus-Based of Emotion (CBE). CBE developed from ANEW and WNA with term similarity measure and distance of node approach. Latent Dirichlet Allocation (LDA) is used too for automatically expand CBE. The CBE attributes are a score of Valence (V), Arousal (A), Dominance (D) and categorical label emotion. Categorical label emotion based on six basic emotion of Ekman. Based on experiment results, it is known that CBE is able to improve the accuracy in detection of emotions. F-Measure using WNA+ANEW is 0.50 and F-Measure using CBE with expanding is 0.61.

Original languageEnglish
Title of host publicationProceedings - 2016 3rd International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2016
EditorsEko Didik Widianto, M. Arfan, Munawar Agus Riyadi, Mochammad Facta
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages331-335
Number of pages5
ISBN (Electronic)9781509014347
DOIs
Publication statusPublished - 4 Apr 2017
Event3rd International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2016 - Semarang, Indonesia
Duration: 19 Oct 201621 Oct 2016

Publication series

NameProceedings - 2016 3rd International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2016

Conference

Conference3rd International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2016
Country/TerritoryIndonesia
CitySemarang
Period19/10/1621/10/16

Keywords

  • ANEW
  • Categorical model
  • Dimensional model
  • Emotion Detection
  • LDA
  • WNA
  • corpus of emotion

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