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A Comparative Study of Sentiment Analysis on Flipkart Dataset using Naïve Bayes Classifier Algorithm
Shanmugapriyaa D, Aravind M S, Sri Bhavan Prakath, S.Deivarani, Rajarajeshwari K
Sentiment analysis, also referred to as sentiment mining, is the process of utilizing computational methods to extract subjective information such as opinions, attitudes, and feelings from textual data. As social media and other online platforms increasingly serve as outlets for expressing emotions and viewpoints, sentiment analysis has become a crucial area of study. This article presents a comprehensive overview of various sentiment analysis techniques and their applications in different fields, including social media analysis. Through machine learning-based techniques, reviews can be classified as positive or negative, and models can be assessed based on metrics such as accuracy, precision, and recall. The article covers rule-based methods, machine learning-based methods, and hybrid approaches, while also addressing the challenges and limitations of sentiment analysis. This resource is valuable for both researchers and practitioners in the field
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