Sentiment 4.0- Deep Learning Based Customer Sentiment Analysis

Abstract

Digital and social media transformation have changed the way business operations, and their customers are managed. Today, it has become challenging to engage and retain customers. It is now necessary to capture and Analyze customer feedback, views, reviews, comments and emotions from different online and social media platforms. Sentiment Analysis {SA} has become an important area of Natural Language Processing {NLP) with the huge amounts of data available on online networks. Sentiment Analysis integrates applications of Natural Language Processing and is a typical classification problem. SA can be done by identifying many features present in texts. Earlier, traditional lexical based techniques, and later, Machine Learning (ML) techniques like regression, were used to analyze sentiment. Today, Deep Learning (DL) techniques like Convoluted Neural Networks (CNN} are being used to solve the SA problem with more accuracy and efficiency. This Chapter discusses the frameworks, tools and techniques available for customer sentiment analysis using Deep Learning techniques. A case study of SA done using the reviews of NPTEL users is also given for clarity.