Term weighting scheme effect in sentiment analysis of online movie reviews
Sentiment analysis is an evolving field of a study that deals directly with the online expressions posted by the user via the Internet with the main objective to automate the process of mining opinions into valuable information. For online reviews, this analysis deals with the identification of posi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Scientific Publishers
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/64689/ http://psasir.upm.edu.my/id/eprint/64689/1/Term%20weighting%20scheme%20effect%20in%20sentiment%20analysis%20of%20online%20movie%20reviews.pdf |
| _version_ | 1848855069756227584 |
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| author | Mat Zin, Harnani Mustapha, Norwati Azmi Murad, Masrah Azrifah Mohd Sharef, Nurfadhlina |
| author_facet | Mat Zin, Harnani Mustapha, Norwati Azmi Murad, Masrah Azrifah Mohd Sharef, Nurfadhlina |
| author_sort | Mat Zin, Harnani |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Sentiment analysis is an evolving field of a study that deals directly with the online expressions posted by the user via the Internet with the main objective to automate the process of mining opinions into valuable information. For online reviews, this analysis deals with the identification of positive and negative reviews to help the consumer and the distributor in the decision-making process. In text analysis tasks, such as text classification and sentiment analysis, the appropriate choice of term weighting schemes will have a huge impact on the effectiveness of the analysis. This paper explores the effect of using term weighting scheme in the sentiment classification of online movie reviews. Specifically, the researchers applied Support Vector Machine (SVM) with linear and non-linear kernels to perform the classification process. The main finding of this study was that LinearSVC when used with TF-IDF improved the classification performance by as much as 87%. Thus, LinearSVC, together with TF-IDF, can serve as an effective technique in the extraction process of online documents. |
| first_indexed | 2025-11-15T11:19:54Z |
| format | Article |
| id | upm-64689 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:19:54Z |
| publishDate | 2018 |
| publisher | American Scientific Publishers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-646892018-08-13T03:45:24Z http://psasir.upm.edu.my/id/eprint/64689/ Term weighting scheme effect in sentiment analysis of online movie reviews Mat Zin, Harnani Mustapha, Norwati Azmi Murad, Masrah Azrifah Mohd Sharef, Nurfadhlina Sentiment analysis is an evolving field of a study that deals directly with the online expressions posted by the user via the Internet with the main objective to automate the process of mining opinions into valuable information. For online reviews, this analysis deals with the identification of positive and negative reviews to help the consumer and the distributor in the decision-making process. In text analysis tasks, such as text classification and sentiment analysis, the appropriate choice of term weighting schemes will have a huge impact on the effectiveness of the analysis. This paper explores the effect of using term weighting scheme in the sentiment classification of online movie reviews. Specifically, the researchers applied Support Vector Machine (SVM) with linear and non-linear kernels to perform the classification process. The main finding of this study was that LinearSVC when used with TF-IDF improved the classification performance by as much as 87%. Thus, LinearSVC, together with TF-IDF, can serve as an effective technique in the extraction process of online documents. American Scientific Publishers 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/64689/1/Term%20weighting%20scheme%20effect%20in%20sentiment%20analysis%20of%20online%20movie%20reviews.pdf Mat Zin, Harnani and Mustapha, Norwati and Azmi Murad, Masrah Azrifah and Mohd Sharef, Nurfadhlina (2018) Term weighting scheme effect in sentiment analysis of online movie reviews. Advanced Science Letters, 24 (2). pp. 933-937. ISSN 1936-6612; ESSN: 1936-7317 https://www.ingentaconnect.com/contentone/asp/asl/2018/00000024/00000002/art00035 10.1166/asl.2018.10661 |
| spellingShingle | Mat Zin, Harnani Mustapha, Norwati Azmi Murad, Masrah Azrifah Mohd Sharef, Nurfadhlina Term weighting scheme effect in sentiment analysis of online movie reviews |
| title | Term weighting scheme effect in sentiment analysis of online movie reviews |
| title_full | Term weighting scheme effect in sentiment analysis of online movie reviews |
| title_fullStr | Term weighting scheme effect in sentiment analysis of online movie reviews |
| title_full_unstemmed | Term weighting scheme effect in sentiment analysis of online movie reviews |
| title_short | Term weighting scheme effect in sentiment analysis of online movie reviews |
| title_sort | term weighting scheme effect in sentiment analysis of online movie reviews |
| url | http://psasir.upm.edu.my/id/eprint/64689/ http://psasir.upm.edu.my/id/eprint/64689/ http://psasir.upm.edu.my/id/eprint/64689/ http://psasir.upm.edu.my/id/eprint/64689/1/Term%20weighting%20scheme%20effect%20in%20sentiment%20analysis%20of%20online%20movie%20reviews.pdf |