Towards Sentiment Analysis Application in Housing Projects
Abdullah, M.R.B. Real Estate Market Structure: Industrial Organization Perspectives. IJMS. 22(1): 57-72. 2015
Osmadi A, E. M. Kamal, H. Hassan, and H. A. Fattah. Exploring the Elements of Housing Price in Malaysia. Asian Social Science. 11: 24-26. 2011.
Nawi, M.N.M., Nifa, F.A.A., Abdullah, S. and Yasin, F.M., 2007,
November. A preliminary survey of the application of Industrialised
Building System (IBS) in Kedah and Perlis Malaysian construction
industry. In Conference on Sustainable Building South East Asia (Vol. 5,
No. 7). 2007.
Liu, B. Sentiment analysis and subjectivity. Handbook of Natural Language Processing, Second Edition. CRC Press, Taylor and Francis Group. 2012.
“Facebook: 10 Years Of Social Networking, In Numbers". the Guardian. N.p. 2014. Web. 9 Feb. 2016.
Craig, S. "170+ Amazing Twitter Statistics". DMR. N.p. 2014. Web. 9
Borth, D., R. Ji, T. Chen, T. Breuel, and S.-F. Chang. Large-scale visual sentiment ontology and detectors using adjective noun pairs. ACM international conference on Multimedia. 223–232. 2013.
Hodson, H. Twitter hashtags predict rising tension in Egypt. New Scientist. 219(2931): 22. 2013.
Ortigosa, A., J. M. Mart´ın, and R. M. Carro. 2014. Sentiment analysis in facebook and its application to e-learning. Computers in Human Behavior. 31: 527–541. 2014.
Pang, B., L. Lee, and S. Vaithyanathan. Thumbs up? Sentiment Classification using Machine Learning Techniques. 7th EMNLP. 79-86. 2002.
Mullen, T., N. Collier. Sentiment Analysis using Support Vector
Machines with Diverse Information Sources. 9th EMNLP. 412-418. 2004.
Turney, P. Thumbs up or thumbs down? semantic orientation applied to unsupervised classifcation of reviews. 40th ACL, pp. 417-424. 2002.
Kudo, T., Y. Matsumoto. A Boosting Algorithm for Classification of Semi-Structured Text. 9th EMNLP, Vol. 4, pp. 301-308. 2004.
Jusoh, S. and Al Fawareh, H.M., 2011. Semantic extraction from texts. InProceedings of International Conference on Computer Engineering and Applications IPCSIT, Singapore. 2011.
Hu, X., J. Tang, H. Gao, and H. Liu. Unsupervised sentiment analysis with emotional signals. International Conference on World Wide Web. 2013.
Yang, B., and C. Cardie. Joint inference for fine-grained opinion extraction. Annual Meeting of the Association for Computational Linguistics. 2013.
Zhou, X., X. Wan, and J. Xiao. Collective opinion target extraction in Chinese microblogs. EMNLP, pp. 1840–1850. 2013.
Lu, Y., Q. Mei, and C. Zhai. 2011. Investigating task performance of probabilistic topic models: an empirical study of plsa and lda. Information Retrieval, 14(2):178–203. 2011.
Choi, Y., and C. Cardie. Hierarchical sequential learning for extracting opinions and their attributes. ACL 2010 Conference Short Papers, pp. 269–274, Stroudsburg, PA, USA. 2010.
Jo, Y., and A. H. Oh. 2011. Aspect and sentiment unification model for online review analysis. WSDM, pages 815–824, New York, NY, USA.
Bansal, M., K. Gimpel, and K. Livescu. 2014. Tailoring continuous word representations for dependency parsing. ACL, pp. 809–815, Baltimore, MD, USA. 2014.
Chen, Y. N., and A. I. Rudnicky. Dynamically supporting unexplored domains in conversational interactions by enriching semantics with neural word embeddings. 2014 Spoken Language Technology Workshop, pp. 590– 595. 2014.
Wang, H., L. Liu, and W. Song. Feature-Based Sentiment Analysis Approach For Product Reviews. Journal of Software. 9(2). 2014.
Samsudin, N., M. Puteh, A. Hamdan, M. Zakree, and A. Nazri. Immune Based Feature Selection for Opinion Mining. World Congress on Engineering. 120-127. 2013.
Puteh, M., N. Isa, S. Puteh, and N. A. Redzuan . Sentiment Mining of Malay Newspaper (SAMNews) Using Artificial Immune System.
Congress on Engineering. 2013.
Das, A., S. Bandyopadhyay, and B. Gamback.. Sentiment analysis: What is the end user’s requirement? WIMS 2012. 35:1–35:10.2012
Dasgupta, S., and V. Ng. 2009. Topic-wise, sentiment-wise, or otherwise?: Identifying the hidden dimension for unsupervised text classification. EMNLP 2009. 580–589. 2009.
Fukuhara, T., H. Nakagawa, and T. Nishida. Understanding sentiment of people from news articles: Temporal sentiment analysis of social events. ICWSM 2007.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.