Machine learning-based Fake reviews detection with amalgamated features extraction method
Product fake reviews are increasing as the trend is changing toward online sales and purchases. Fake review detection is critical and challenging for both researchers and online retailers. As new techniques are introduced to catch the fake reviewer, so are their intruding approaches. In this paper,...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sukkur IBA University
2023-01-01
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| Series: | Sukkur IBA Journal of Emerging Technologies |
| Online Access: | http://journal.iba-suk.edu.pk:8089/sibajournals/index.php/sjet/article/view/1091 |
| _version_ | 1797959569655201792 |
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| author | Muhammad Bux Alvi Majdah Alvi Rehan Ali Shah Mubashira Munir Adnan Akhtar |
| author_facet | Muhammad Bux Alvi Majdah Alvi Rehan Ali Shah Mubashira Munir Adnan Akhtar |
| author_sort | Muhammad Bux Alvi |
| collection | DOAJ |
| description |
Product fake reviews are increasing as the trend is changing toward online sales and purchases. Fake review detection is critical and challenging for both researchers and online retailers. As new techniques are introduced to catch the fake reviewer, so are their intruding approaches. In this paper, different features are amalgamated along with sentiment score to design a model that checks the model performance under different classifiers. For this purpose, six supervised learning algorithms are utilized to build the fake review detection models, utilizing LIWC, unigrams, and sentiment score features. Results show that the amalgamation of selected features is a better approach to fake review detection, achieving an accuracy score of 88.76%, which is promising compared to similar other work.
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| first_indexed | 2024-04-11T00:33:32Z |
| format | Article |
| id | doaj.art-24f936beba0b400cbe7a1285c51fe70c |
| institution | Directory Open Access Journal |
| issn | 2616-7069 2617-3115 |
| language | English |
| last_indexed | 2024-04-11T00:33:32Z |
| publishDate | 2023-01-01 |
| publisher | Sukkur IBA University |
| record_format | Article |
| series | Sukkur IBA Journal of Emerging Technologies |
| spelling | doaj.art-24f936beba0b400cbe7a1285c51fe70c2023-01-07T03:11:38ZengSukkur IBA UniversitySukkur IBA Journal of Emerging Technologies2616-70692617-31152023-01-015210.30537/sjet.v5i2.1091Machine learning-based Fake reviews detection with amalgamated features extraction methodMuhammad Bux Alvi0Majdah Alvi1Rehan Ali Shah2Mubashira Munir3Adnan Akhtar4The Islamia University of BahawalpurThe Islamia University of BahwalpurThe Islamia University of BahwalpurThe Islamia University of BahwalpurThe Islamia University of Bahwalpur Product fake reviews are increasing as the trend is changing toward online sales and purchases. Fake review detection is critical and challenging for both researchers and online retailers. As new techniques are introduced to catch the fake reviewer, so are their intruding approaches. In this paper, different features are amalgamated along with sentiment score to design a model that checks the model performance under different classifiers. For this purpose, six supervised learning algorithms are utilized to build the fake review detection models, utilizing LIWC, unigrams, and sentiment score features. Results show that the amalgamation of selected features is a better approach to fake review detection, achieving an accuracy score of 88.76%, which is promising compared to similar other work. http://journal.iba-suk.edu.pk:8089/sibajournals/index.php/sjet/article/view/1091 |
| spellingShingle | Muhammad Bux Alvi Majdah Alvi Rehan Ali Shah Mubashira Munir Adnan Akhtar Machine learning-based Fake reviews detection with amalgamated features extraction method Sukkur IBA Journal of Emerging Technologies |
| title | Machine learning-based Fake reviews detection with amalgamated features extraction method |
| title_full | Machine learning-based Fake reviews detection with amalgamated features extraction method |
| title_fullStr | Machine learning-based Fake reviews detection with amalgamated features extraction method |
| title_full_unstemmed | Machine learning-based Fake reviews detection with amalgamated features extraction method |
| title_short | Machine learning-based Fake reviews detection with amalgamated features extraction method |
| title_sort | machine learning based fake reviews detection with amalgamated features extraction method |
| url | http://journal.iba-suk.edu.pk:8089/sibajournals/index.php/sjet/article/view/1091 |
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