Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid System
Nowadays, most decision processes rely not only on the preferences of the decision maker but also on the public opinions about the possible alternatives. The user preferences have been heavily taken into account in the multi-criteria decision making field. On the other hand, sentiment analysis is th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/1/216 |
| _version_ | 1827699116474368000 |
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| author | Mohammed Jabreel Najlaa Maaroof Aida Valls Antonio Moreno |
| author_facet | Mohammed Jabreel Najlaa Maaroof Aida Valls Antonio Moreno |
| author_sort | Mohammed Jabreel |
| collection | DOAJ |
| description | Nowadays, most decision processes rely not only on the preferences of the decision maker but also on the public opinions about the possible alternatives. The user preferences have been heavily taken into account in the multi-criteria decision making field. On the other hand, sentiment analysis is the field of natural language processing devoted to the development of systems that are capable of analysing reviews to obtain their polarity. However, there have not been many works up to now that integrate the results of this process with the analysis of the alternatives in a decision support system. SentiRank is a novel system that takes into account both the preferences of the decision maker and the public online reviews about the alternatives to be ranked. A new mechanism to integrate both aspects into the ranking process is proposed in this paper. The sentiments of the reviews with respect to different aspects are added to the decision support system as a set of additional criteria, and the ELECTRE methodology is used to rank the alternatives. The system has been implemented and tested with a restaurant data set. The experimental results confirm the appeal of adding the sentiment information from the reviews to the ranking process. |
| first_indexed | 2024-03-10T13:43:26Z |
| format | Article |
| id | doaj.art-447c599fe0ab4fb596155f6b671e1630 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T13:43:26Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-447c599fe0ab4fb596155f6b671e16302023-11-21T02:51:06ZengMDPI AGApplied Sciences2076-34172020-12-0111121610.3390/app11010216Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid SystemMohammed Jabreel0Najlaa Maaroof1Aida Valls2Antonio Moreno3ITAKA Research Group, Universitat Rovira i Virgili, 43007 Tarragona, SpainITAKA Research Group, Universitat Rovira i Virgili, 43007 Tarragona, SpainITAKA Research Group, Universitat Rovira i Virgili, 43007 Tarragona, SpainITAKA Research Group, Universitat Rovira i Virgili, 43007 Tarragona, SpainNowadays, most decision processes rely not only on the preferences of the decision maker but also on the public opinions about the possible alternatives. The user preferences have been heavily taken into account in the multi-criteria decision making field. On the other hand, sentiment analysis is the field of natural language processing devoted to the development of systems that are capable of analysing reviews to obtain their polarity. However, there have not been many works up to now that integrate the results of this process with the analysis of the alternatives in a decision support system. SentiRank is a novel system that takes into account both the preferences of the decision maker and the public online reviews about the alternatives to be ranked. A new mechanism to integrate both aspects into the ranking process is proposed in this paper. The sentiments of the reviews with respect to different aspects are added to the decision support system as a set of additional criteria, and the ELECTRE methodology is used to rank the alternatives. The system has been implemented and tested with a restaurant data set. The experimental results confirm the appeal of adding the sentiment information from the reviews to the ranking process.https://www.mdpi.com/2076-3417/11/1/216opinion miningsentiment analysisaspect-based sentiment analysismultiple criteria decision aid |
| spellingShingle | Mohammed Jabreel Najlaa Maaroof Aida Valls Antonio Moreno Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid System Applied Sciences opinion mining sentiment analysis aspect-based sentiment analysis multiple criteria decision aid |
| title | Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid System |
| title_full | Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid System |
| title_fullStr | Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid System |
| title_full_unstemmed | Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid System |
| title_short | Introducing Sentiment Analysis of Textual Reviews in a Multi-Criteria Decision Aid System |
| title_sort | introducing sentiment analysis of textual reviews in a multi criteria decision aid system |
| topic | opinion mining sentiment analysis aspect-based sentiment analysis multiple criteria decision aid |
| url | https://www.mdpi.com/2076-3417/11/1/216 |
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