ISBN: 978-981-09-5471-0 DOI: 10.18178/wcse.2015.04.104
Opinion Mining on Twitter Data for Airline Services
Abstract— Opinion mining on Twitter data for airline services is a valuable application which assists
user in collecting messages expressing the positive opinion or the negative comment. The objective of
the application is to analyze messages about airline services on Twitter data by sentiment analysis.
The proposed technique uses information about syntax and semantics of words in the message to
define features before learning by Naïve Bayes and generate the classification model. Then, this
application can classify opinions or comments about the airline services on the variety of Twitter
messages. Therefore, customers of airline services can know how good the service quality is. In
addition, the airline service providers can improve services by customer satisfaction and also meet
customer requirements. Furthermore, the application can help users to collect the information to make
a decision for airline services. The result of application performance testing shows that the accuracy
and the precision are about 70%.
Index Terms— Twitter, opinion mining, sentiment analysis, subjectivity analysis.
Pakawan Pugsee, Tuangrath Chongvisuit, Kananant Na Nakorn
Innovative Network and Software Engineering Technology Laboratory, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, THAILAND
Cite: Pakawan Pugsee, Tuangrath Chongvisuit, Kananant Na Nakorn, "Opinion Mining on Twitter Data for Airline Services," 2015 The 5th International Workshop on Computer Science and Engineering-Information Processing and Control Engineering (WCSE 2015-IPCE), pp. 639-644, Moscow, Russia, April 15-17, 2015.