Opinion Mining On Web-Based Communities Using Optimised Clustering Algorithms

Abstract

People like to consume content by downloading it from the internet, together with contribution and creation of new content, thanks to the growth of social networks and the Web. People also turn out to be more anxious to communicate and impart their insights on the web with respect to everyday exercises or worldwide issues. Sentiment analysis and opinion mining are rapidly evolving as a result of the rapid growth of web-based platforms such as Facebook, Reddit, Twitter, and others. This is from the world of data mining and NLP, especially in the mining of web data and the mining of texts. Why has sentiment analysis been more popular in recent years, which is also known as opinion mining? Whenever we attempt to choose to buy an item, we are probably going to hear the thoughts of companions or family members and do a few overviews before we buy the item. Opinions are now undoubtedly the main drivers of our behavior. The positive, negative, or neutral polarities are consistently seen in the opinions. Opinion mining can be used to discover opinion polarity classification, subjectivity identification, spam detection, and opinion summarization using emotional classification.