Abstract
Sentiment Analysis, pivotal in natural language processing, extends its reach beyond English to Indian regional languages like Hindi, Marathi, Kannada, Konkani, Bengali, Khandeshi, and Urdu. This paper presents a comprehensive survey of 32 research papers in this domain, examining methodologies, datasets, and techniques while emphasizing the significance of sentiment analysis in diverse linguistic contexts for enhancing customer relationship management functionalities. It underscores the necessity for future research and highlights the efficacy of machine learning techniques. By elucidating on computational challenges and outlining various sentiment analysis methods, this paper serves as a critical resource for researchers and practitioners, fostering advancements in sentiment analysis tailored to regional linguistic nuances. KEYWORDS Bag Of Words, Hindi, Kannada, RNN, Konkani, Malayalam, Marathi, Maximum Entropy, Naive Bayes, Sentiment Analysis, SVM, TF-IDF, Urdu.
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