Sentiment analysis : A survey on design framework, applications and future scopes
© The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript v...
| Publié dans: | Artificial intelligence review. - 1998. - (2023) vom: 20. März, Seite 1-56 |
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| Auteur principal: | |
| Autres auteurs: | |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2023
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| Accès à la collection: | Artificial intelligence review |
| Sujets: | Journal Article Knowledge representation Natural language processing Sentiment analysis Text analysis |
| Résumé: | © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Sentiment analysis is a solution that enables the extraction of a summarized opinion or minute sentimental details regarding any topic or context from a voluminous source of data. Even though several research papers address various sentiment analysis methods, implementations, and algorithms, a paper that includes a thorough analysis of the process for developing an efficient sentiment analysis model is highly desirable. Various factors such as extraction of relevant sentimental words, proper classification of sentiments, dataset, data cleansing, etc. heavily influence the performance of a sentiment analysis model. This survey presents a systematic and in-depth knowledge of different techniques, algorithms, and other factors associated with designing an effective sentiment analysis model. The paper performs a critical assessment of different modules of a sentiment analysis framework while discussing various shortcomings associated with the existing methods or systems. The paper proposes potential multidisciplinary application areas of sentiment analysis based on the contents of data and provides prospective research directions |
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| Description: | Date Revised 28.09.2023 published: Print-Electronic Citation Status Publisher |
| ISSN: | 0269-2821 |
| DOI: | 10.1007/s10462-023-10442-2 |