Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study
In the last decade, sentiment analysis has been widely applied in many domains, including business, social networks and education. Particularly in the education domain, where dealing with and processing students’ opinions is a complicated task due to the nature of the language used by students and t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/9/3986 |
| _version_ | 1827693958165168128 |
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| author | Zenun Kastrati Fisnik Dalipi Ali Shariq Imran Krenare Pireva Nuci Mudasir Ahmad Wani |
| author_facet | Zenun Kastrati Fisnik Dalipi Ali Shariq Imran Krenare Pireva Nuci Mudasir Ahmad Wani |
| author_sort | Zenun Kastrati |
| collection | DOAJ |
| description | In the last decade, sentiment analysis has been widely applied in many domains, including business, social networks and education. Particularly in the education domain, where dealing with and processing students’ opinions is a complicated task due to the nature of the language used by students and the large volume of information, the application of sentiment analysis is growing yet remains challenging. Several literature reviews reveal the state of the application of sentiment analysis in this domain from different perspectives and contexts. However, the body of literature is lacking a review that systematically classifies the research and results of the application of natural language processing (NLP), deep learning (DL), and machine learning (ML) solutions for sentiment analysis in the education domain. In this article, we present the results of a systematic mapping study to structure the published information available. We used a stepwise PRISMA framework to guide the search process and searched for studies conducted between 2015 and 2020 in the electronic research databases of the scientific literature. We identified 92 relevant studies out of 612 that were initially found on the sentiment analysis of students’ feedback in learning platform environments. The mapping results showed that, despite the identified challenges, the field is rapidly growing, especially regarding the application of DL, which is the most recent trend. We identified various aspects that need to be considered in order to contribute to the maturity of research and development in the field. Among these aspects, we highlighted the need of having structured datasets, standardized solutions and increased focus on emotional expression and detection. |
| first_indexed | 2024-03-10T11:54:36Z |
| format | Article |
| id | doaj.art-f4f7cb193da14517ba4d85968378dd5d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T11:54:36Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-f4f7cb193da14517ba4d85968378dd5d2023-11-21T17:29:50ZengMDPI AGApplied Sciences2076-34172021-04-01119398610.3390/app11093986Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping StudyZenun Kastrati0Fisnik Dalipi1Ali Shariq Imran2Krenare Pireva Nuci3Mudasir Ahmad Wani4Faculty of Technology, Linnaeus University, 351 95 Växjö, SwedenFaculty of Technology, Linnaeus University, 351 95 Växjö, SwedenFaculty of Information Technology and Electrical Engineering, Norwegian University of Science & Technology (NTNU), 2815 Gjøvik, NorwayFaculty of Computer Science and Engineering, University for Business and Technology, 10000 Prishtine, KosovoFaculty of Information Technology and Electrical Engineering, Norwegian University of Science & Technology (NTNU), 2815 Gjøvik, NorwayIn the last decade, sentiment analysis has been widely applied in many domains, including business, social networks and education. Particularly in the education domain, where dealing with and processing students’ opinions is a complicated task due to the nature of the language used by students and the large volume of information, the application of sentiment analysis is growing yet remains challenging. Several literature reviews reveal the state of the application of sentiment analysis in this domain from different perspectives and contexts. However, the body of literature is lacking a review that systematically classifies the research and results of the application of natural language processing (NLP), deep learning (DL), and machine learning (ML) solutions for sentiment analysis in the education domain. In this article, we present the results of a systematic mapping study to structure the published information available. We used a stepwise PRISMA framework to guide the search process and searched for studies conducted between 2015 and 2020 in the electronic research databases of the scientific literature. We identified 92 relevant studies out of 612 that were initially found on the sentiment analysis of students’ feedback in learning platform environments. The mapping results showed that, despite the identified challenges, the field is rapidly growing, especially regarding the application of DL, which is the most recent trend. We identified various aspects that need to be considered in order to contribute to the maturity of research and development in the field. Among these aspects, we highlighted the need of having structured datasets, standardized solutions and increased focus on emotional expression and detection.https://www.mdpi.com/2076-3417/11/9/3986sentiment analysisopinion miningstudent feedbackuser reviewsteacher assessmenteducational platforms |
| spellingShingle | Zenun Kastrati Fisnik Dalipi Ali Shariq Imran Krenare Pireva Nuci Mudasir Ahmad Wani Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study Applied Sciences sentiment analysis opinion mining student feedback user reviews teacher assessment educational platforms |
| title | Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study |
| title_full | Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study |
| title_fullStr | Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study |
| title_full_unstemmed | Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study |
| title_short | Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study |
| title_sort | sentiment analysis of students feedback with nlp and deep learning a systematic mapping study |
| topic | sentiment analysis opinion mining student feedback user reviews teacher assessment educational platforms |
| url | https://www.mdpi.com/2076-3417/11/9/3986 |
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