Distortion Detection on Online Social Networks using Proficient Sentiment Analysis for Banking Institutions

Social media data has been extensively employed in the banking institutions in order to improve the product and service development, customer service, marketing, risk management and business performance. The online social networks such as Facebook, Twitter, etc are considered for analysis. To build the social media strategies, bank needs customer to drive trustworthiness, revenue and success is all about the customer experience. The approach employed Natural Language Processing (NLP) for social media intelligence retrieval. Then based on the concept of sentiment analysis, the customer opinions are categorized for efficient decision making. Thus the NLP & sentiment analysis can be employed for improving banking service for better customer satisfaction.