Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses

Chih-Hao Ku, Yung-Chun Chang, Yichuan Wang, Chien-Hung Chen, Shih-Hui Hsiao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With a growing number of online reviews, consumers often rely on these reviews to make purchase decisions. However, little is known about managerial responses to online hotel reviews. This paper reports on a framework to integrate visual analytics and machine learning techniques to investigate whether hotel managers respond to positive and negative reviews differently and how to use a deep-learning approach to prioritize responses. In this study, forty 4-and 5-star hotels in London with 91,051 reviews and 70,397 responses were collected and analyzed. Visual analyses and machine learning were conducted. The results indicate most hotels (72.5%) showing no preference to respond to positive and negative reviews. Our proposed deep-learning approach outperformed existing algorithms to prioritize responses.
Original languageEnglish
Title of host publication52nd Hawaii International Conference on System Sciences
Publication statusPublished - Jan 8 2019

Cite this

Ku, C-H., Chang, Y-C., Wang, Y., Chen, C-H., & Hsiao, S-H. (2019). Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses. In 52nd Hawaii International Conference on System Sciences

Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses. / Ku, Chih-Hao; Chang, Yung-Chun; Wang, Yichuan; Chen, Chien-Hung; Hsiao, Shih-Hui.

52nd Hawaii International Conference on System Sciences . 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ku, C-H, Chang, Y-C, Wang, Y, Chen, C-H & Hsiao, S-H 2019, Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses. in 52nd Hawaii International Conference on System Sciences .
Ku C-H, Chang Y-C, Wang Y, Chen C-H, Hsiao S-H. Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses. In 52nd Hawaii International Conference on System Sciences . 2019
Ku, Chih-Hao ; Chang, Yung-Chun ; Wang, Yichuan ; Chen, Chien-Hung ; Hsiao, Shih-Hui. / Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses. 52nd Hawaii International Conference on System Sciences . 2019.
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AB - With a growing number of online reviews, consumers often rely on these reviews to make purchase decisions. However, little is known about managerial responses to online hotel reviews. This paper reports on a framework to integrate visual analytics and machine learning techniques to investigate whether hotel managers respond to positive and negative reviews differently and how to use a deep-learning approach to prioritize responses. In this study, forty 4-and 5-star hotels in London with 91,051 reviews and 70,397 responses were collected and analyzed. Visual analyses and machine learning were conducted. The results indicate most hotels (72.5%) showing no preference to respond to positive and negative reviews. Our proposed deep-learning approach outperformed existing algorithms to prioritize responses.

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