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Sentiment and opinion analysis on twitter about local airlines

Abstract:

Social media allow the users to express and share their information, ideas and opinions through social networking sites. Airline tweets are becoming popular and used as dataset to gauge the concerns of the customers. In this paper, the researchers classified a tweet’s polarity through annotation using classifiers Naïve Bayesian, Support Vector Machine and Random Forest to develop a model. The researchers gathered tweets of local airlines concerning their experience in the services provided by local airlines in the Philippines. The researchers also determined the sentiment of a tweet if it is positive, neutral or negative and provided the quantitative and qualitative analyses, as well as opinion analysis, to better understand the result of the experiment.