Document Type
Dissertation
Rights
This item is available under a Creative Commons License for non-commercial use only
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE
Abstract
In the field of sentiment classification, much research has been done on reviews of topics such as movies, software and books. Little research has been done in the airline service domain. In the airline industry, the use of social media as a customer service tool has become a growing phenomenon. The research conducted by Wan and Gao (2015) has proposed an ensemble classification approach for airline service sentiment classification using Twitter data. In accordance, the objective of improving the performance of ensemble classification approach is the primary consideration. This research proposed new hybrid classification approach that uses the state-of-art approach proposed by Wan and Gao (2015) combining with lexicon based approach on classification of airline service topic using Twitter data. The research evaluated the proposed approach in depth, along with explorations of implementing expansion of tweet content in order to further improve the classification performance. In this project, the ensemble approach that consists of both machine learning approaches and lexicon based approach was analysed which suggested the improvement of the proposed classification approach performance compare with machine learning only approach on airline service domain conducted by Wan and Gao (2015).
DOI
https://doi.org/10.21427/D7190M
Recommended Citation
Wang, Z (2016) The evaluation of ensemble sentiment classification approach on airline services using Twitter. Masters dissertation, Technological University Dublin, 2017. doi:10.21427/D7190M
Publication Details
Dissertation submitted in partial fulfillment of the requirements of Technological University Dublin for the degree of M.Sc. in Computing (Advanced Software Computing) 2017.