Empirical Study on Sentiment Analysis
Creators
- 1. Associate Professor, Department of Computer Science and Engineering, SRM Institute of Science & Technology, Ramapuram (Tamil Nadu), India.
Contributors
Contact person:
Researchers:
- 1. Associate Professor, Department of Computer Science and Engineering, SRM Institute of Science & Technology, Ramapuram (Tamil Nadu), India.
- 2. Assistant Professor, Department of Computing, Vellore Institute of Technology, Andhra Pradesh, India.
- 3. Professor, Department of Computer Science and Engineering, Jain Deemed to be University, Bangalore (Karnataka), India
- 4. Research Scholar, Department of Computer Science and Engineering, SRM Institute of Science & Technology, Ramapuram (Tamil Nadu), India.
Description
Abstract: Sentiment analysis (SA), generally known as Opinion Mining (OM), is really the process of gathering and evaluating people's ideas, thoughts, feelings, beliefs, including views about various subjects, goods, as well as services. Individuals produce large amounts of comments and evaluations about products, services, and day-to-day tasks as Internet-based applications such as webpages, online sites, social networking sites, and blog posts continue to evolve at a rapid pace. Firms, government institutions medical researchers and scholars may use sentiment analysis to collect and evaluate mood of the people and perspectives, obtain business information, and make smarter and more informed choices. The approaches for sentiment analysis are thoroughly examined in this work, problems, trends and features in order to provide academics with a worldwide overview of sentiment analysis and topics of interest. The paper discusses the various uses of sentiment analysis as well as the general procedure for performing this assignment. The report subsequently examines, analyses, and analyses the various techniques in order to gain a comprehensive understanding of its benefits and downsides. Furthermore, to elucidate long term prospects, the constraints of sentiment analysis have been highlighted.
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Additional details
Identifiers
- DOI
- 10.54105/ijainn.B1044.123122
- EISSN
- 2582-7626
Dates
- Accepted
-
2022-12-15Manuscript received on 23 December 2021 | Revised Manuscript received on 10 December 2022 | Manuscript Accepted on 15 December 2022 | Manuscript published on 30 December 2023
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