HOTEL GUEST REVIEWS AS A TOOL OF COMPETITIVE ADVANTAGE

  • Cvetko Andreeski Faculty of Tourism and Hospitality – Ohrid

Abstract

According to the research of many authors, guest reviews are important source of data used for different types of analysis which can support decision making process in hotel industry. Guest reviews are important for both tourists and hotel managers. The analyses of the reviews are main issue in detecting weaknesses in tourism offer. There are many questions before we can start the analysis of guest reviews and take data from these reviews. Text analysis such as text processing, text classification and sentiment analysis, metadata, statistical and econometric analysis can give good feedback of the quality of service in tourism. In this, paper we do the analysis of the relevance of guest reviews and propose a framework for sentiment analysis.

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References

1. Agheorghiesei, D. T., Ineson, E. (2011). The Impact of Online Booking Systems on Customer Loyalty in Romania. Journal of Tourism, 45-54.
2. Andreeski, C. (2015). Sentiment Analysis in Tourism. ETAI 2015 (p. A2), ETAI Organization, Ohrid.
3. Andreeski, C. (2015). Steps towards statistical and sentiment analysis on guest reviews. MiPro, MiPro Croatian Society, Opatijia.
4. Andreeski, C. (2016). Iterative Framework on upgrading Lexicons for Sentiment Analysis. ETAI (pp. AM-1), ETAI Association, Struga.
5. Bogdanovych, A., Berger, H., Simoff, S., Sierra, C., Hitz, M., Sigala, M., Murphy, J. (2006). Travel agents vs. online booking: tackling the shortcomings of nowadays online tourism portals. International Conference on Information and Communication Technologies in Tourism, Springer, Lausanne, 418-428.
6. Chang, J., Boyd-Graber, J., Chong, W., Gerrish, S., Blei, D. (2009). Reading Tea Leaves: How Humans Interpret Topic Models. Proceedings of Neural Information Processing Systems, Vancouver, 288-296.
7. Chen, Z., Mukherjee, A., Liu, B. (2014). Aspect Extraction with Automated Prior Knowledge Learning. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics Association for Computational Linguistics, Baltimore, 347-358.
8. Diaz, M. R., Rodriguez, T. E. (2017). A methodology for a comparative analysis of the lodging offer of tourism destinations based on online customer reviews. Journal of Destination Marketing & Management, http://dx.doi.org/10.1016/j.jdmm.2017.02.006.
9. Dietmar, G., Markus, Z., Gunther, F., Matthias, F. (2012). Classification of Customer Reviews based on Sentiment Analysis. 19th Conference on Information and Communication Technologies in Tourism. Helsingborg.
10. Kasper, W., Vela, M. (2011). Sentiment Analysis for Hotel Reviews. Proceedings of the Computational Linguistics-Applications Conference, Katowice, 45-52.
11. Lazaridou, A., Titov, I., Sporleder, C. (2013). A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations. Annual Meeting of the Assiciation for Computational Linguistics, 1630-1639.
12. Pang, B., Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, Vol. 2, No. 1, 1-135.
13. Proserpio, D., Zevas, G. (2016). Online reputation management: Estimating the impact of management responses on consumer reviews. Marketing Science, 1-43.
14. Ruths, D., Pfeffer, J. (2014). Social media for large studies of behavior. Science 346, 1063-1064.
15. Sparks, B., Browning, V. (2011). The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management, Vol. 32, No. 6, 1310-1323.
16. Xiang, Z., Du, Q., Ma, Y., Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, Vol. 58, 51-65.
17. Zhang, Z., Singh, M. (2014). A Semi-Supervised Framework for Generating Domain-Specific Lexicons and Sentiment Analysis. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 542-551.
18. Zhiyuan, C., Arjun, M., Bing, L. (2014). Aspect Extraction with Automated Prior Knowledge Learning. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics, Baltimore, 347-358.
19. Јовиќ, Ј. (2016). Утицај информационе технологије на рад туристичких агенција. In Ј. Јовиќ. Охрид: ФТУ-Охрид.
20. Стефановски, С. (2016). Улогата и влијанието на информатичко-комуникациските технологии во охридските хотели. In С. Стефановски. Охрид: ФТУ - Охрид.
Published
2017-06-03
How to Cite
Andreeski, C. (2017). HOTEL GUEST REVIEWS AS A TOOL OF COMPETITIVE ADVANTAGE. TISC - Tourism International Scientific Conference Vrnjačka Banja, 2(1), 1-21. Retrieved from http://www.tisc.rs/proceedings/index.php/hitmc/article/view/129