Exploring the Applications of Natural Language Processing for Text Analysis: A Focus on Sentiment Analysis

Abstract— Researchers have focused a lot of emphasis in the last 10 years on sentiment analysis, the automatic extraction of expressions of positive or negative sentiments from text. Regarding people, groups, locations, occasions, and ideas, they have both positive and negative attitudes. It is now possible to start extracting feelings from websites thanks to the tools given by natural language processing and machine learning as well as other methods to work with massive amounts of material. In this paper, we discuss some of the difficulties in sentiment extraction, some of the approaches that have been used to overcome these difficulties, and our approach that analyses sentiments from user feedbacks and produces results that go beyond just polarity but use those polarities in service profiling and quality. The approach can be improved based on promising results, which demonstrate that sentiment analysis in websites can be used to meet the needs of the business environment