Sentiment Analysis Using Text Mining: A Survey
International Research Journal of Modernization in Engineering Technology and Science · 2023
Sentiment analysis, also known as opinion mining, is a data mining technique used to extract and analyze sentiments expressed in textual data.It involves automatically determining the polarity (positive, negative, or neutral) of opinions or emotions conveyed in a large volume of text.By applying various natural language processing and machine learning algorithms, sentiment analysis enables the identification and classification of sentiments in an automated and scalable manner.This technique has gained significant importance due to the exponential growth of user-generated content on social media platforms, product reviews, customer feedback, and other sources.The abstract of sentimental analysis using data mining encapsulates the extraction of sentiments from text data, providing insights into public opinion, customer satisfaction, brand perception, and emerging trends.By analyzing sentiments, businesses can make data-driven decisions, improve customer experiences, detect emerging issues, and tailor their products or services to meet customer needs more effectively.