ARCHIVES
Original Article
Deep Learning-Based Sentiment Analysis of Hotel Reviews Using LSTM and Bidirectional LSTM Models
Kadupu Durga Prasad1
Patinavalasa Durga Prasad2
Suneel Kumar Duvvuri3
1 2 Students, Department of Computer Science, Government College (Autonomous), Rajahmundry, Andhra Pradesh, India. 3 Assistant Professor, Department of Computer Science, Government College (Autonomous), Rajahmundry, Andhra Pradesh, India.
Published Online: January-April 2026
Pages: 262-272
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20260501038
References
1. Z. Xiang and U. Gretzel, “Role of Social Media in Online Travel Information Search,” Tour. Manag., vol. 31, pp. 179–188, Mar. 2010, doi:
10.1016/j.tourman.2009.02.016.
2. S. W. Litvin, R. E. Goldsmith, and S. Litvin, “ELECTRONIC WORD-OF-MOUTH IN HOSPITALITY AND TOURISM
MANAGEMENT.”
3. Q. Ye, R. Law, and B. Gu, “The impact of online user reviews on hotel room sales,” Int. J. Hosp. Manag., vol. 28, no. 1, pp. 180–182, Mar.
2009, doi: 10.1016/j.ijhm.2008.06.011.
4. J. A. Chevalier and D. Mayzlin, “THE EFFECT OF WORD OF MOUTH ON SALES: ONLINE BOOK REVIEWS,” 2003. [Online].
Available: http://www.nber.org/papers/w10148
5. C. Dellarocas, “MIT Sloan School of Management THE DIGITIZATION OF WORD-OF-MOUTH: PROMISE AND CHALLENGES OF
ONLINE FEEDBACK MECHANISMS THE DIGITIZATION OF WORD-OF-MOUTH: PROMISE AND CHALLENGES OF ONLINE
FEEDBACK MECHANISMS,” 2003. [Online]. Available: http://ssrn.com/abstract=393042
6. B. Liu, “Sentiment Analysis and Opinion Mining,” Morgan & Claypool Publishers, 2012.
7. J. Prager, “Open-domain question-answering,” Foundations and Trends in Information Retrieval, vol. 1, no. 2, pp. 91–233, 2006, doi:
10.1561/1500000001.
8. E. Cambria, B. Schuller, Y. Xia, and C. Havasi, “New avenues in opinion mining and sentiment analysis,” IEEE Intell. Syst., vol. 28, no. 2,
pp. 15–21, 2013, doi: 10.1109/MIS.2013.30.
9. Sheffield and York, Who cares about sarcastic tweets? Investigating the impact of sarcasm on sentiment analysis. 2014.
10. M. Taboada, J. Brooke, M. Tofiloski, K. Voll, and M. Stede, “Lexicon-Based Methods for Sentiment Analysis,” 2011.
11. B. Pang, L. Lee, and S. Vaithyanathan, “Thumbs up? Sentiment Classification using Machine Learning Techniques.” [Online]. Available:
http://reviews.imdb.com/Reviews/
12. G. Salton and C. Buckley, “Term Weighting Approaches in Automatic Text Retrieval,” Ithaca, New York, USA, Nov. 1987.
13. Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” May 27, 2015, Nature Publishing Group. doi: 10.1038/nature14539.
14. I. Goodfellow, Y. Bengio, and A. Courville, “Deep Learning.”
15. J. L. Elman, “Finding Structure in Time,” Cogn. Sci., vol. 14, no. 2, pp. 179–211, Mar. 1990, doi: 10.1207/s15516709cog1402_1.
16. S. Hochreiter and J. Schmidhuber, “Long Short-Term Memory,” Neural Comput., vol. 9, no. 8, pp. 1735–1780, 1997.
17. M. Schuster and K. K. Paliwal, “Bidirectional Recurrent Neural Networks,” IEEE Transactions on Signal Processing, vol. 45, no. 11, pp.2673–2681, 1997, doi: 10.1109/78.650093.
18. X. Zhang and Y. LeCun, “Text Understanding from Scratch,” Apr. 2016, [Online]. Available: http://arxiv.org/abs/1502.01710
19. W. Medhat, A. Hassan, and H. Korashy, “Sentiment analysis algorithms and applications: A survey,” Ain Shams Engineering Journal, vol.
5, no. 4, pp. 1093–1113, Dec. 2014, doi: 10.1016/j.asej.2014.04.011.
20. T. Young, D. Hazarika, S. Poria, and E. Cambria, “Recent Trends in Deep Learning Based Natural Language Processing,” Nov. 2018,
[Online]. Available: http://arxiv.org/abs/1708.02709
21. D. Buhalis and R. Law, “Tourism Management Reviews Progress in tourism management Twenty years on and 10 years after the Internet:
The state of eTourism research.” [Online]. Available: http://www.bournemouth.ac.uk/services-management/
22. U. Gretzel and K. H. Yoo, “Use and Impact of Online Travel Reviews.”
23. B. Liu, Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers, 2012. doi: 10.2200/S00416ED1V01Y201204HLT016.
24. T. Hennig-Thurau, K. P. Gwinner, G. Walsh, and D. D. Gremler, “Electronic Word-of-Mouth via Consumer-Opinion Platforms: What
Motivates Consumers to Articulate Themselves on the Internet?,” Journal of Interactive Marketing, vol. 18, no. 1, pp. 38–52, 2004, doi:
10.1002/dir.10073.
25. Q. Ye, Q. Li, and R. Law, “The Impact of Online User Reviews on Hotel Room Sales,” Int. J. Hosp. Manag., vol. 28, no. 1, pp. 180–182,
2009, doi: 10.1016/j.ijhm.2008.06.011.
26. R. Filieri and F. McLeay, “E-WOM and Accommodation: An Analysis of the Factors That Influence Travelers’ Adoption of Information
from Online Reviews,” J. Travel Res., vol. 53, no. 1, pp. 44–57, 2014, doi: 10.1177/0047287513481274.
27. Z. Zhang, Q. Ye, and R. Law, “Determinants of hotel room price: An exploration of travelers’ hierarchy of accommodation needs,” Oct.
2011. doi: 10.1108/09596111111167551.
28. S. W. Litvin, R. E. Goldsmith, and S. Litvin, “ELECTRONIC WORD-OF-MOUTH IN HOSPITALITY AND TOURISM
MANAGEMENT.”
29. B. Pang and L. Lee, “Opinion Mining and Sentiment Analysis,” Foundations and Trends in Information Retrieval, vol. 2, no. 1–2, pp. 1–135,
2008, doi: 10.1561/1500000011.
30. T. Joachims, “Text Categorization with Support Vector Machines: Learning with Many Relevant Features,” in Proceedings of the European
Conference on Machine Learning (ECML), Springer, 1998, pp. 137–142. doi: 10.1007/BFb0026683.
31. Y. Goldberg, Neural Network Methods for Natural Language Processing. in Synthesis Lectures on Human Language Technologies. Morgan
& Claypool Publishers, 2017. doi: 10.2200/S00762ED1V01Y201703HLT037.
32. S. Hochreiter and J. Schmidhuber, “Long Short-Term Memory,” Neural Comput., vol. 9, no. 8, pp. 1735–1780, 1997, doi:
10.1162/neco.1997.9.8.1735.
33. M. Schuster and K. K. Paliwal, “Bidirectional Recurrent Neural Networks,” IEEE Transactions on Signal Processing, vol. 45, no. 11, pp.
2673–2681, 1997, doi: 10.1109/78.650093.
10.1016/j.tourman.2009.02.016.
2. S. W. Litvin, R. E. Goldsmith, and S. Litvin, “ELECTRONIC WORD-OF-MOUTH IN HOSPITALITY AND TOURISM
MANAGEMENT.”
3. Q. Ye, R. Law, and B. Gu, “The impact of online user reviews on hotel room sales,” Int. J. Hosp. Manag., vol. 28, no. 1, pp. 180–182, Mar.
2009, doi: 10.1016/j.ijhm.2008.06.011.
4. J. A. Chevalier and D. Mayzlin, “THE EFFECT OF WORD OF MOUTH ON SALES: ONLINE BOOK REVIEWS,” 2003. [Online].
Available: http://www.nber.org/papers/w10148
5. C. Dellarocas, “MIT Sloan School of Management THE DIGITIZATION OF WORD-OF-MOUTH: PROMISE AND CHALLENGES OF
ONLINE FEEDBACK MECHANISMS THE DIGITIZATION OF WORD-OF-MOUTH: PROMISE AND CHALLENGES OF ONLINE
FEEDBACK MECHANISMS,” 2003. [Online]. Available: http://ssrn.com/abstract=393042
6. B. Liu, “Sentiment Analysis and Opinion Mining,” Morgan & Claypool Publishers, 2012.
7. J. Prager, “Open-domain question-answering,” Foundations and Trends in Information Retrieval, vol. 1, no. 2, pp. 91–233, 2006, doi:
10.1561/1500000001.
8. E. Cambria, B. Schuller, Y. Xia, and C. Havasi, “New avenues in opinion mining and sentiment analysis,” IEEE Intell. Syst., vol. 28, no. 2,
pp. 15–21, 2013, doi: 10.1109/MIS.2013.30.
9. Sheffield and York, Who cares about sarcastic tweets? Investigating the impact of sarcasm on sentiment analysis. 2014.
10. M. Taboada, J. Brooke, M. Tofiloski, K. Voll, and M. Stede, “Lexicon-Based Methods for Sentiment Analysis,” 2011.
11. B. Pang, L. Lee, and S. Vaithyanathan, “Thumbs up? Sentiment Classification using Machine Learning Techniques.” [Online]. Available:
http://reviews.imdb.com/Reviews/
12. G. Salton and C. Buckley, “Term Weighting Approaches in Automatic Text Retrieval,” Ithaca, New York, USA, Nov. 1987.
13. Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” May 27, 2015, Nature Publishing Group. doi: 10.1038/nature14539.
14. I. Goodfellow, Y. Bengio, and A. Courville, “Deep Learning.”
15. J. L. Elman, “Finding Structure in Time,” Cogn. Sci., vol. 14, no. 2, pp. 179–211, Mar. 1990, doi: 10.1207/s15516709cog1402_1.
16. S. Hochreiter and J. Schmidhuber, “Long Short-Term Memory,” Neural Comput., vol. 9, no. 8, pp. 1735–1780, 1997.
17. M. Schuster and K. K. Paliwal, “Bidirectional Recurrent Neural Networks,” IEEE Transactions on Signal Processing, vol. 45, no. 11, pp.2673–2681, 1997, doi: 10.1109/78.650093.
18. X. Zhang and Y. LeCun, “Text Understanding from Scratch,” Apr. 2016, [Online]. Available: http://arxiv.org/abs/1502.01710
19. W. Medhat, A. Hassan, and H. Korashy, “Sentiment analysis algorithms and applications: A survey,” Ain Shams Engineering Journal, vol.
5, no. 4, pp. 1093–1113, Dec. 2014, doi: 10.1016/j.asej.2014.04.011.
20. T. Young, D. Hazarika, S. Poria, and E. Cambria, “Recent Trends in Deep Learning Based Natural Language Processing,” Nov. 2018,
[Online]. Available: http://arxiv.org/abs/1708.02709
21. D. Buhalis and R. Law, “Tourism Management Reviews Progress in tourism management Twenty years on and 10 years after the Internet:
The state of eTourism research.” [Online]. Available: http://www.bournemouth.ac.uk/services-management/
22. U. Gretzel and K. H. Yoo, “Use and Impact of Online Travel Reviews.”
23. B. Liu, Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers, 2012. doi: 10.2200/S00416ED1V01Y201204HLT016.
24. T. Hennig-Thurau, K. P. Gwinner, G. Walsh, and D. D. Gremler, “Electronic Word-of-Mouth via Consumer-Opinion Platforms: What
Motivates Consumers to Articulate Themselves on the Internet?,” Journal of Interactive Marketing, vol. 18, no. 1, pp. 38–52, 2004, doi:
10.1002/dir.10073.
25. Q. Ye, Q. Li, and R. Law, “The Impact of Online User Reviews on Hotel Room Sales,” Int. J. Hosp. Manag., vol. 28, no. 1, pp. 180–182,
2009, doi: 10.1016/j.ijhm.2008.06.011.
26. R. Filieri and F. McLeay, “E-WOM and Accommodation: An Analysis of the Factors That Influence Travelers’ Adoption of Information
from Online Reviews,” J. Travel Res., vol. 53, no. 1, pp. 44–57, 2014, doi: 10.1177/0047287513481274.
27. Z. Zhang, Q. Ye, and R. Law, “Determinants of hotel room price: An exploration of travelers’ hierarchy of accommodation needs,” Oct.
2011. doi: 10.1108/09596111111167551.
28. S. W. Litvin, R. E. Goldsmith, and S. Litvin, “ELECTRONIC WORD-OF-MOUTH IN HOSPITALITY AND TOURISM
MANAGEMENT.”
29. B. Pang and L. Lee, “Opinion Mining and Sentiment Analysis,” Foundations and Trends in Information Retrieval, vol. 2, no. 1–2, pp. 1–135,
2008, doi: 10.1561/1500000011.
30. T. Joachims, “Text Categorization with Support Vector Machines: Learning with Many Relevant Features,” in Proceedings of the European
Conference on Machine Learning (ECML), Springer, 1998, pp. 137–142. doi: 10.1007/BFb0026683.
31. Y. Goldberg, Neural Network Methods for Natural Language Processing. in Synthesis Lectures on Human Language Technologies. Morgan
& Claypool Publishers, 2017. doi: 10.2200/S00762ED1V01Y201703HLT037.
32. S. Hochreiter and J. Schmidhuber, “Long Short-Term Memory,” Neural Comput., vol. 9, no. 8, pp. 1735–1780, 1997, doi:
10.1162/neco.1997.9.8.1735.
33. M. Schuster and K. K. Paliwal, “Bidirectional Recurrent Neural Networks,” IEEE Transactions on Signal Processing, vol. 45, no. 11, pp.
2673–2681, 1997, doi: 10.1109/78.650093.
Related Articles
2026
Artificial Intelligence in Learning and Teaching
2026
Admin Assist: An AI – Driven Configuration and Orchestration for Enterprise Application
2026
Enhancing Blood Group Identification using pigeon inspired optimization: An Innovative Approach
2026
Eco-Genius: Power Up Smart, Power Down Waste
2026
Crowd-Sourced Disaster Response and Rescue Assistant
2026
