Airline Attitudes: Mining Data for Service Sentiment Insights

Published user reviews and opinions underlie sentiment analysis, thereby enabling extraction of essential data about service providers and indicating their market status. This study investigates smell sentimental grouping precision of standard information mining systems against six Indian carriers related social media microblog datasets. The sentiment analysis with classifiers, namely Bayes Net and SVM, achieved good results in their accuracies. The analysis centers on how well passenger sentiments can be separated out by the six airlines. On WEKA tool, Bayes Net gained the highest accuracy whereas on Rapid Miner tool, SVM yields better classification than all others. A look at passengers experience with the airlines According to reviews, Go Air has been one of the top-knotch in terms of service received by customers and turns out to be highest rated airline based on passenger feedback.