Machine learning-based sentiment analysis of Gujarati reviews

Parita Shah and Priya Swaminarayan

International Journal of Data Analysis Techniques and Strategies, 2022, vol. 14, issue 2, 105-121

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.

Keywords: N-gram; feature selection; sentiment evaluation; Gujarati language; film analysis; machine classifier. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:ids:injdan:v:14:y:2022:i:2:p:105-121

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