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Pavan K A

Dr K Jothi

Abstract

Sentiment analysis, also known as opinion mining, is a natural language processing (NLP) technique used to determine the sentiment or emotional tone expressed in a piece of text. The goal of sentiment analysis is to identify whether the sentiment conveyed in the text is positive, negative, or neutral. NLP is to enable computers to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant. The primary objective of sentiment analysis is to understand and interpret the sentiment or emotional tone expressed in a piece of text. Sentiment analysis is widely used in various industries and businesses to gain insights into public opinion, customer feedback, and market trends. This helps in improving product recommendations, managing inventory, and enhancing the overall shopping experience. Social media and Marketing use sentiment analysis in social media platforms to gauge the success of marketing campaigns, track brand sentiment, and identify trends. Social media sentiment analysis helps in shaping marketing strategies and maintaining a positive brand image. In Healthcare organizations use sentiment analysis to analyse patient feedback, reviews, and comments about healthcare services. This can assist in improving patient satisfaction, identifying areas for improvement, and enhancing overall healthcare delivery. In conclusion sentiment analysis serves as a powerful tool for extracting meaningful information from textual data, offering a deeper understanding of human expressions and opinions. Its widespread adoption across industries reflects its transformative impact on decision-making, customer relations, and overall business strategies.

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