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The International Conference on Artificial Intelligence and Computer Vision

AICV 2020: Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) pp 405–413Cite as

Machine Learning-Based Sentiment Analysis for Analyzing the Travelers Reviews on Egyptian Hotels

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1153))

Abstract

Tourism affects the economy of any country; actually, it is the foundation of the country on the economic side. Egyptian Government is giving a big concern in developing the tourism sector. Hotel companies are using E-commerce technology for online booking and online reviewing. Travelers choose hotels based on their prices, facilities and other traveler’s review. Sentiment analysis is a very important topic that can be used to analyze the opinion of online users. Different websites are classifying the traveler reviews such as Tripadvisor, Expedia. The research aims to propose a Traveler Review Sentiment Classifier that will analyze the traveler’s reviews on Egyptian Hotels and provide a classification of each sentiment based on hotel features. Travelers Sentiment about five hotels located in Aswan in Egypt with a total of 11458 reviews were collected and analyzed. Sentiment model uses three classification techniques: Support Vector Machine, Naive Bayes and Decision Tree. Results had shown that Naïve Bayes has the highest accuracy level.

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References

  1. Ye, Q., Law, R., Gu, B.: The impact of online user reviews on hotel room sales. Int. J. Hosp. Manag. 28(1), 180–182 (2009)

    Article  Google Scholar 

  2. Zhang, X., Qiaoa, S., Yang, Y., Ziqiong, Z.: Exploring the impact of personalized management responses on tourists’ satisfaction: atopic matching perspective. Tour. Manag. 76(2020), 103953 (2020)

    Article  Google Scholar 

  3. Changa, Y., Kuc, C., Chend, C.: Social media analytics: extracting and visualizing Hilton hotel ratings and reviews from TripAdvisor. Int. J. Inf. Manag. 48, 263–279 (2019)

    Article  Google Scholar 

  4. Boo, S., Busser, J.A.: Meeting planners’ online reviews of destination hotels: a twofold content analysis approach. Tour. Manag. 66(6), 287–301 (2018)

    Article  Google Scholar 

  5. Hua, F., Trivedi, R.: Mapping hotel brand positioning and competitive landscapes by text-mining user-generated content. Int. J. Hosp. Manag. 84, 102317 (2020)

    Article  Google Scholar 

  6. Calı, S., Balaban, S.: Improved decisions for marketing, supply, and purchasing: Mining big data through the integration of sentiment analysis and intuitionistic fuzzy multi-criteria assessment. Comput. Ind. Eng. 129, 315–332 (2019)

    Article  Google Scholar 

  7. Hermitian, F., Sohrabi, M.K.: A survey on classification techniques for opinion mining and sentiment analysis. Artif. Intell. Rev. 1, 1–51 (2017)

    Google Scholar 

  8. Daud, A., Khan, W., Che, D.: Urdu Language Processing: A Survey. Kluwer Academic Publishers, Alphen aan denrijn (2017)

    Google Scholar 

  9. Weiler, B., Walker, K.: Enhancing the visitor experience: reconceptualising the tour guide’s communicative role. J. Hosp. Tour. Manag. 21(21), 90–99 (2014)

    Article  Google Scholar 

  10. Raisi, H., Baggio, R., Barratt-Pugh, L., Willson, G.: Hyperlink network analysis fa tourism destination. J. Travel Res. 57(2), 1–27 (2017)

    Google Scholar 

  11. Schouten, K., Frasincar, F.: Survey on aspect-level sentiment analysis. IEEE Trans. Knowl. Data Eng. 28(3), 813–830 (2016)

    Article  Google Scholar 

  12. Abdi, A., Shamsuddin, S.M., Hasan, S., Piran, J.: Machine learning-based multi documents sentiment-oriented summarization using linguistic treatment. Expert Syst. Appl. 109, 66–85 (2018)

    Article  Google Scholar 

  13. Raut, V.B., Londhe, D.D.: Opinion mining and summarization of hotel reviews. In: Proceedings - 2014 6th International Conference on Computational Intelligence and Communication Networks, pp. 556–559 (2014)

    Google Scholar 

  14. Dehkharghani, R., Yanikoglu, B., Tapucu, D., Saygin, Y.: Adaptation and use of subjectivity lexicons for domain-dependent sentiment classification. In: IEEE 12th International Conference on Data Mining Workshops Adaptation, pp. 669–673 (2012)

    Google Scholar 

  15. Smetana, M., Koncz, P., Smetana, P., Parali, J.: Active learning enhanced semiautomatic annotation tool for aspect-based sentiment analysis. In: IEEE 11th International Symposium on Intelligent Systems and Informatics, pp. 191–194 (2013)

    Google Scholar 

  16. Najmi, E., Hashmi, K., Malik, Z., Rezgui, A., Khan, H.U.: CAPRA: a comprehensive approach to product ranking using customer reviews. Computing 97(8), 843–867 (2015)

    Article  MathSciNet  Google Scholar 

  17. Mostafa, L., Abd Elghany, M.: Investigating game developers’ guilt emotions using sentiment analysis. Int. J. Softw. Eng. Appl. (IJSEA), 9(6), (2018)

    Google Scholar 

  18. Mostafa, L., Farouk, M., Fakhry, M.: An automated approach for webpage classification. In: ICCTA 2009 Proceedings of the 19th International Conference on Computer Theory and Applications, Alexandria, Egypt (2009)

    Google Scholar 

  19. Abdelghany, M., Abdelghany, M., Mostafa, L.: The analysis of the perceptions of service facilities and their impact on student satisfaction. In: IJBR, vol. 19, no. 1 (2019)

    Google Scholar 

  20. Knime. http://www.knime.com/. Accessed 11 Sept 2019

  21. Chatterjee, S.: Drivers of the helpfulness of online hotel reviews: A sentiment and emotion mining approach. Int. J. Hosp. Manag. (2019)

    Google Scholar 

  22. Kim, D., Park, B.J.: The moderating role of context in the effects of choice attributes on hotel choice: a discrete choice experiment. Tour. Manag. 63, 439–451 (2017)

    Article  Google Scholar 

  23. Yadav, M., Roychoudhury, B.: Effect of trip mode on opinion about hotel aspects: a social media analysis approach. Int. J. Hosp. Manag. 80, 155–165 (2019)

    Article  Google Scholar 

  24. Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up?: sentiment classification using machine learning techniques. In: Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing, vol. 10, pp. 79–86 (2002)

    Google Scholar 

  25. Chang, C., Lin, C.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2(3), 27 (2011)

    Google Scholar 

  26. Suresh, A.: Sentiment classification using decision tree-based feature selection. Int. J. Control Theory Appl. 9, 419–425 (2016)

    Google Scholar 

  27. Xiang, Z., Schwartz, Z., Gerdes Jr., J.H., Uysal, M.: What can big data and text analytics tell us about hotel guest experience and satisfaction? Int. J. Hosp. Manag. 44(44), 120–130 (2015)

    Article  Google Scholar 

  28. Zhang, F., Song, Y., Cai, W., Liu, S., Liu, S., Pujol, S., Feng, D.D.: Pairwise latent semantic association for similarity computation in medical imaging. IEEE (2016)

    Google Scholar 

  29. Korovkinas, K., Dennis, P., Garšva, G.: SVM and Naïve Bayes classification ensemble method for sentiment analysis. Baltic J. Mod. Comput. 5(4), 398–409 (2017)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Business Information System Department, Arab Academy for Science and Technology and Maritime Transport, Alexandria, Egypt

    Lamiaa Mostafa

Authors
  1. Lamiaa Mostafa
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Corresponding author

Correspondence to Lamiaa Mostafa .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Faculty of Computers and Information, Giza, Egypt

    Aboul-Ella Hassanien

  2. Faculty of Computers and Information, Benha University, Banha, Egypt

    Ahmad Taher Azar

  3. Faculty of Computers and Information, Suez Canal University, Ismailia, Egypt

    Tarek Gaber

  4. Departamento de Ciencias Computacionales, Universidad de Guadalajara, CUCEI, Guadajalara, Jalisco, Mexico

    Diego Oliva

  5. Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Fahmy M. Tolba

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Cite this paper

Mostafa, L. (2020). Machine Learning-Based Sentiment Analysis for Analyzing the Travelers Reviews on Egyptian Hotels. In: Hassanien, AE., Azar, A., Gaber, T., Oliva, D., Tolba, F. (eds) Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020). AICV 2020. Advances in Intelligent Systems and Computing, vol 1153. Springer, Cham. https://doi.org/10.1007/978-3-030-44289-7_38

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