Machine learning-based sentiment analysis of Gujarati reviews
Source
International Journal of Data Analysis Techniques and Strategies
ISSN
17558050
Date Issued
2022-01-01
Author(s)
Shah, Parita
Swaminarayan, Priya
Abstract
Opinion examination is the investigation of applied information in an articulation, like appraisals, assessments, sentiments, or perspectives toward a point, individual, or component. Positive, negative, and unbiased articulations are altogether conceivable. The authors of this exploration have built a dataset of Gujarati film audits and give the discoveries produced by the proposed calculation message in the wake of performing sentiment examination utilising a five different machine classifier. The authors fostered various datasets to test our calculation's capacities with different machine classifiers. This paper clarifies how information was gathered to shape a dataset, as well as Gujarati text pre-handling, include determination, and order techniques. According to the results of the investigation, all of the classifiers are performing brilliantly, generating overall precision greater than 75%, however KNN is unable to produce preferred precision above the others.
Subjects
feature selection | film analysis | Gujarati language | machine classifier | N-gram | sentiment evaluation
