Sentiment analysis from travellers’ reviews using enhanced conjunction rule based approach for feature-specific evaluation of hotels

References

• B. Sarkar, N. Sinhababu, M. Roy, P. K. D. Pramanik and P. Choudhury, “Mining Multilingual and Multiscript Twitter Data: Unleashing the Language and Script Barrier,” International Journal of Business Intelligence and Data Mining, vol. 16, no. 1, pp. 107-127, 2020.
   Google Scholar
• W. Li, L. Zhu, K. Guo, Y. Shi and Y. Zheng, “Build a Tourism-Specific Sentiment Lexicon Via Word2vec,” Annals of Data Science, vol. 5, no. 1, pp. 1-7, 2018.
   Google Scholar
• H.-X. Shi and X.-J. Li, “A sentiment analysis model for hotel reviews based on supervised learning,” in International Conference on Machine Learning and Cybernetics, Guilin, China, 2011.
   Google Scholar
• M. T. Khan, M. Durrani, K. H. Khan, A. Ali and S. Khalid, “Aspect-based Sentiment Analysis on a Large-Scale Data: Topic Models are the Preferred Solution,” Bahria University Journal of Information & Communication Technologies, vol. 8, no. 2, pp. 22-27, 2015.
   Google Scholar
• O. Kolchyna, T. T. P. Souza, P. Treleaven and T. Aste, “Twitter Sentiment Analysis: Lexicon Method, Machine Learning Method and Their Combination,” in Handbook of Sentiment Analysis in Finance, G. Mitra and X. Yu, Eds., Albury Books, 2016, pp. 1-30.
   Google Scholar
• A. Jadeja and I. J. Rajput, “Feature Based Sentiment Analysis On Customer Feedback: A Survey,” International Journal of Engineering Research & Technology, vol. 2, no. 4, pp. 2246-2253, 2013.
   Google Scholar
• Q. Ye, Z. Zhang and R. Law, “Sentiment classification of online reviews to travel destinations by supervised machine learning approaches,” Expert Systems with Applications, vol. 36, no. 3 (Part 2), pp. 6527-6535, 2009.
   Web of Science ®Google Scholar
• M. D. Devika, C. Sunitha and A. Ganesh, “Category Based Sentiment Analysis in Travel And Tourism Domain,” IOSR Journal of Computer Engineering (IOSR-JCE), vol. 1, pp. 1-5, 2016.
   Google Scholar
• A. Bali, D. Harsole, N. M. Zaman and P. Agarwal, “Consumer’s Sentiment Analysis of Popular Phone Brands and Operating System Preference,” International Journal of Computer Applications, vol. 155, no. 4, pp. 15-19, 2016.
   Google Scholar
• A. R. Alaei, S. Becken and B. Stantic, “Sentiment Analysis in Tourism: Capitalizing on Big Data,” Journal of Travel Research, vol. 58, no. 2, pp. 175-191, 2019.
   Web of Science ®Google Scholar
• M. Afzaal and . M. Usman, “A Novel Framework for Aspect-based Opinion Classification for Tourist Places,” in The Tenth International Conference on Digital Information Management(ICDIM 2015), 2015.
   Google Scholar
• X. Fang and J. Zhan, “Sentiment analysis using product review data,” Journal of Big Data, vol. 2 (Article number: 5), pp. 1-14, 2015.
   Google Scholar
• M. P. Anto, M. Antony, K. M. Muhsina, N. Johny, V. James and A. Wilson, “Product rating using sentiment analysis,” in International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, India, 2016.
   Google Scholar
• S. M. Vohra and J. B. Teraiya, “A Comparative Study of Sentiment Analysis Techniques,” Journal of Information, Knowledge and Research in Computer Engineering, vol. 2, no. 2, pp. 313-317, 2013.
   Google Scholar
• J. Eisenstein, “Unsupervised Learning for Lexicon-Based Classification,” in Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, USA, 2016.
   Google Scholar
• S. Gao, J. Hao and Y. Fu, “The Application and Comparison of Web Services for Sentiment Analysis in Tourism,” in 12th International Conference on Service Systems and Service Management (ICSSSM), Guangzhou, China, 2015.
   Google Scholar
• Y. Fu, J.-X. Hao, X. Li and H. C. H. Cathy, “Predictive Accuracy of Sentiment Analytics for Tourism: A Metalearning Perspective on Chinese Travel News,” Journal of Travel Research, vol. 58, no. 4, pp. 666–679, 2019.
   Web of Science ®Google Scholar
• Z. Hailong, G. Wenyan and J. Bo, “Machine Learning and Lexicon Based Methods for Sentiment Classification: A Survey,” in 11th Web Information System and Application Conference, Tianjin, China, 2014.
   Google Scholar
• T. Pedersen, S. Patwardhan and J. Michelizzi, “WordNet:: Similarity: measuring the relatedness of concepts,” in HLT-NAACL 2004, Boston, 2004.
   Google Scholar
• S. Loria, “TextBlob: Simplified Text Processing,” TextBlob, December 2018. [Online]. Available: https://textblob.readthedocs.io/en/dev/#. [Accessed 29 December 2019].
   Google Scholar