Sentiment Analysis Of Tweets Using Natural Language Processing

Abstract

– Millions of people use Twitter and other social media sites to share their everyday thoughts in the form of tweets. It is a short and straightforward way of expressing oneself, which is a hallmark of tweeting. As a result, we concentrated on sentiment analysis of Twitter data in our research. Sentiment Analysis is a subset of natural language processing and text data mining. It is feasible to investigate sentiment analysis using Twitter data. performed in a number of different circumstances The technique of finding valuable patterns from textual data is referred to as sentiment analysis. Using particular analysis tools, these valuable patterns include evaluating and categorizing feelings as neutral, positive, or negative. The study's authors look at a range of information processing approaches, including sentiment analysis, Twitter's network structure, event dispersion across the network, and impact identification. There have been several ways described for exploring semantics for sentiment analysis, which can be classified into contextual semantic and conceptual semantic approaches. One of the most important disciplines of natural language processing is sentiment analysis. The technique of finding valuable patterns from textual data is referred to as sentiment analysis. According to this research, sentiment analysis applications will continue to develop in the future, and sentiment analytical approaches will become more standardized across systems and services. Because of the vast amount of data available, Twitter is one of the best virtual environments for tracking and monitoring information.