Abstract
Twitter is one of the most popular applications for sharing feelings and opinions. Sentiment analysis also known as opinion mining is basically used to classify text into three or more categories: positive, negative and neutral sentiments. In this study, sentiment analysis is tested on tweets about www.booking.com in Turkey after the court decided to stop the activities of Booking.com. Moreover, after the date that Booking.com stops its services, traffic data of other major Web sites serving in this sector has been obtained and how they are influenced by this activity is also interpreted. As a result of the literature, sentiment analysis on English texts is a highly popular and well-studied topic; however, it has been observed that the study of text mining in Turkish language is limited. The data is obtained on Twitter from starting the date that Booking.com closures in Turkey. The Twitter messages in Turkish were manually obtained from the Internet because of being expensive of old tweet data. The data has been passed through the preprocessing, attribute selection and classification stages. At the end of these processes, the data is analyzed using various text mining algorithms so the success rates achieved are compared and interpreted.
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Akkol, E., Alici, S., Aydin, C., Tarhan, C. (2020). What Happened in Turkey After Booking.com Limitation: Sentiment Analysis of Tweets via Text Mining. In: Janowicz-Lomott, M., Łyskawa, K., Polychronidou, P., Karasavvoglou, A. (eds) Economic and Financial Challenges for Balkan and Eastern European Countries. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-39927-6_18
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