Publication:
Opinion classification on a social network by a novel feature selection technique

dc.contributor.authorChoompol, Atchara
dc.contributor.authorSongram, Panida
dc.contributor.authorChomphuwiset, Phattahanaphong
dc.date.accessioned2023-12-16T10:57:10Z
dc.date.available2023-12-16T10:57:10Z
dc.date.issued2020
dc.date.issuedBE2563
dc.description.abstractMost of the opinion comments on social networks are short and ambiguous. In general; opinion classification on the comments is difficult because of lacking dominant features. A feature extraction technique is therefore necessary for improving accuracy of the classification and computational time. This paper proposes an effective feature selection method for opinion classification on a social network. The proposed method selects features based on the concept of a filter model; together with association rules. Support and confidence are used to calculate the weights of features. The features with high weight are selected for classification. Unlike supports in association rules; supports in our method are normalized to 0-1 to remove outlier supports. Moreover; a tuning parameter is used to emphasize the degree of support or confidence. The experimental results show that the proposed method provides high classification efficiency. The proposed method outperforms Information Gain; Chi-Square; and Gini Index in both computational time and accuracy.
dc.identifier.doi10.11591/ijeecs.v20.i2.pp960-967
dc.identifier.issn2502-4760
dc.identifier.urihttps://harrt.in.th/handle/123456789/8539
dc.language.isoen
dc.rightsCopyright (c) 2020 Institute of Advanced Engineering and Science
dc.subjectการจำแนกประเภทความคิดเห็น
dc.subjectการทำเหมืองข้อมูล
dc.subjectเครือข่ายสังคม
dc.subjectAssociation Rule
dc.subjectFeature Selection
dc.subjectOpinion Classification
dc.subjectOpinion Mining
dc.subjectSocial Network
dc.subject.isced0322 บรรณารักษ์, สารสนเทศ และการศึกษาจดหมายเหตุ
dc.subject.oecd5.8 นิเทศศาสตร์และสื่อสารมวลชน
dc.titleOpinion classification on a social network by a novel feature selection technique
dc.typeบทความวารสาร (Journal Article)
dspace.entity.typePublication
harrt.researchAreaสารสนเทศศาสตร์
harrt.researchGroupบรรณารักษศาสตร์และสารสนเทศศาสตร์
harrt.researchTheme.1Data Science
harrt.researchTheme.2Data Mining
mods.location.urlhttps://ijeecs.iaescore.com/index.php/IJEECS/article/view/21318
oaire.citation.endPage967
oaire.citation.issue2
oaire.citation.startPage960
oaire.citation.titleIndonesian Journal of Electrical Engineering and Computer Science
oaire.citation.volume20
oairecerif.author.affiliationมหาวิทยาลัยมหาสารคาม. คณะวิทยาการสารสนเทศ. ภาควิชาวิทยาการคอมพิวเตอร์
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