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A Hierarchical Emotion Classification Technique for Thai Reviews

Journal of ICT Research and Applications (JICTRA) · Vol. 12 No. 3 (2018) · pp. 280–296

DOI
10.5614/itbj.ict.res.appl.2018.12.3.6
ISSN
2338-5499, 2337-5787
Published
2018-12-31
Publisher
DRI - ITB
Language
eng

Abstract

Emotion classification is an interesting problem in affective computing that can be applied in various tasks, such as speech synthesis, image processing and text processing. With the increasing amount of textual data on the Internet, especially reviews of customers that express opinions and emotions about products. These reviews are important feedback for companies. Emotion classification aims to identify an emotion label for each review. This research investigated three approaches for emotion classification of opinions in the Thai language, written in unstructured format, free form or informal style. Different sets of features were studied in detail and analyzed. The experimental results showed that a hierarchical approach, where the subjectivity of the review is determined first, then the polarity of opinion is identified and finally the emotional label is calculated, yielded the highest performance, with precision, recall and F-measure at 0.691, 0.743 and 0.709, respectively.

Keywords

Collaboration network of the authors

7 authors · 6 co-authorship links · 1 across different organisations

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  • National Institute of Development Administration
  • Kasetsart University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Ajay ArunachalamAffiliation unknown2
Theerapol LimsattaNational Institute of Development Administration1
Kanyanut HomsapayaNational Institute of Development Administration1
Knitchepon ChotchantarakunNational Institute of Development Administration1
Chalothon ChootongKasetsart University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">A Hierarchical Emotion Classification Technique for Thai Reviews</dc:title>
	<dc:creator>Charoensuk, Jirawan</dc:creator>
	<dc:creator>Sornil, Ohm</dc:creator>
	<dc:subject xml:lang="en-US">hierarchical emotion classification</dc:subject>
	<dc:subject xml:lang="en-US">speech synthesis</dc:subject>
	<dc:subject xml:lang="en-US">opinion classification</dc:subject>
	<dc:subject xml:lang="en-US">text processing</dc:subject>
	<dc:subject xml:lang="en-US">Thai language</dc:subject>
	<dc:description xml:lang="en-US">Emotion classification is an interesting problem in affective computing that can be applied in various tasks, such as speech synthesis, image processing and text processing. With the increasing amount of textual data on the Internet, especially reviews of customers that express opinions and emotions about products. These reviews are important feedback for companies. Emotion classification aims to identify an emotion label for each review. This research investigated three approaches for emotion classification of opinions in the Thai language, written in unstructured format, free form or informal style. Different sets of features were studied in detail and analyzed. The experimental results showed that a hierarchical approach, where the subjectivity of the review is determined first, then the polarity of opinion is identified and finally the emotional label is calculated, yielded the highest performance, with precision, recall and F-measure at 0.691, 0.743 and 0.709, respectively.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2018-12-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/9154</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2018.12.3.6</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 12 No. 3 (2018); 280-296</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/9154/3849</dc:relation>
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