Determination of Twitter Users Sentiment Polarity Toward Airline Market in Turkey: a Case of Opinion Mining

Abstract

The identification of actual and potential customers opinions and sentiments before and after purchase shapes the services offered by airlines in the airline sector as well as in every sector. In this paper, a sentiment analysis is made by compiling Twitter users' comments related to air transport. Comments of users collected from API (Application Programming Interfaces) service provided by Twitter as with many social media applications and were taken from a Java based program on a regular basis between April-May 2016. Obtained 8672 user comments were decomposed as positive, notr and negative tags. Tags are collected in a tag cloud and results are analysed with Machine Learning Method and standardized and normalized Kernel Polinoms in SMO algorithm.