A LITERATURE REVIEW: CUSTOMER SATISFACTION ON AIRLINE TWEETS USING MACHINE LEARNING

Computer Engineering

Nowadays social media gains lots of popularity for expressing their views and for other services. Consumer sentiment analysis is a recent fad for social media related applications such as healthcare, crime, finance, travel, and academics. Twitter is one of the most prominent social networking platforms so far. Millions of users utilize Twitter to share their thoughts and views on various topics of interest every day resulting a huge amount of data. Sentiment Analysis is new way of machine learning to extract opinion orientation (positive, negative, neutral) from a text segment written for any product, organization and all other entities. In this research work, we present the review of literature related to the customer satisfaction on airline tweets using machine learning and also explaining the different machine learning approach which gives customer satisfaction for the social media (Tweets).

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