Sentiment Analysis: A comparative Analysis of Machine learning models
Sentiment analysis (SA) is the process of Finding or adding a meaning to a text using natural language processing, a deep examination of data that is maintained online at various platforms such as movie reviews, product reviews at different online shopping apps, twitter (now X), etc., to recognize and classify the opinions and ideas that are expressed in a certain passage of text. The process's aim is to search for the author's perspective on a certain topic, film, item, etc. The outcome can be neutral, bad, or good. There have been studies that demonstrated various methods in the SA methodology for gathering and analysing feelings related to the selected subjects’ polarity—positive, negative, or neutral. Social media SA is a reliable source of data and information. SA becomes significant in a variety of business, social, and academic fields. The evaluation and sentiment analysis process, however, is looked upon with difficulties. Finding the proper side of polarity and accurately interpreting sentiments that are hindered by these difficulties. Sentiment analysis is a part of natural language processing and used text mining to find and evaluate the bias from the text.
Authors
- Ishanvi Singh
- Aditya Verma
- Abhishek Kumar (ORCID: https://orcid.org/0000-0002-9326-1474)
- Satya P. Yadav (ORCID: https://orcid.org/0000-0001-6646-7787)
- Jaspreet Kaur (ORCID: https://orcid.org/0000-0002-2883-9241)
- Aryan Panwar
Institutions
- Bennett University (IN)
- JRE Group of Institutions (IN)
- Graphic Era University (IN)
- Punjab Engineering College (IN)
Publication Details
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1109/ihcsp63227.2024.10959760
- Primary Topic
- Sentiment Analysis and Opinion Mining
- Type
- article
- Field-Weighted Citation Impact
- 0.00