Analysing Customers Sentiments: An Approach to Opinion Mining and Classification of Online Hotel Reviews
Customer opinion holds a very important place in products and service business, especially for companies and potential customers. In the last years, opinions have become yet more important due to global Internet usage as opinions pool. Unfortunately , looking through customer reviews and extracting information to improve their service is a difficult work due to the large number of existing reviews. In this work we present a system designed to mine client opinions, classify them as positive or negative, and classify them according to the hotel features they belong to. To obtain this classification we use a machine learning classifier, reinforced with lexical resources to extract polarity and a specialized hotel features taxonomy.
KeywordsNatural Language Processing Opinion Mining Sentiment Analysis Word Sense Lexical Resource
Unable to display preview. Download preview PDF.
- 1.Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Computational Linguistics (2011)Google Scholar
- 2.Dave, K., Lawrence, S., Pennock, D.: Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In: Proceedings of the 12th International Conference on World Wide Web, WWW 2003 (2003)Google Scholar
- 3.Huang, J., Etzioni, O., Zettlemoyer, L., Clark, K., Lee, C.: RevMiner: An Extractive Interface for Navigating Reviews on a Smartphone. In: Proceedings of the 25th ACM Symposium on User Interface Software and Technology (2012)Google Scholar
- 4.Zhuang, L., Jing, F., Zhu, X.-Y., Zhang, L.: Movie review mining and summarization. In: Proceedings of the ACM SIGIR Conference on Information and Knowledge Management, CIKM (2006)Google Scholar
- 5.Agerri, R., García-Serrano, A.: Q-WordNet: Extracting Polarity from WordNet Senses. In: Proceedings of the Seventh Conference on International Language Resources and Evaluation (2010)Google Scholar