Author : Enimai V 1
Date of Publication :21st April 2017
Abstract: Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral. It’s also known as opinion mining, deriving the opinion or attitude of a speaker .It is used to identify the mood emotional tone of the speaker. Sentiment analysis is extremely useful in social media monitoring as it allows us to gain the idea of the public. The problem is hard to find the motive of the sentence. The data source is twitter using twitter API. The techniques used are term frequency(TF), inverse document frequency(IDF) and Support vector machine(SVM) which is used to seperate the positive, negative and neutral.
Reference :
-
- B. Pang, L. Lee, and S. Vaithyanathan, “Thumbs up?: sentiment classifi- cation using machine learning techniques,” in Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10. Association for Computational Linguistics, 2002, pp. 79– 86.
- J. Erman, M. Arlitt, and A. Mahanti, “Traffic classification using clustering algorithms,” in Proceedings of the 2006 SIGCOMM workshop on Mining network data. ACM, 2006, pp. 281–286.
- A. Kyriakopoulou and T. Kalamboukis, “Text classification using clustering,” in Proceedings of The 17th European Conference on Machine Learning and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Burlin, Germany, 2006, pp. 28–38.
- N. Slonim, N. Friedman, and N. Tishby, “Unsupervised document classification using sequential information maximization,” in Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, 2002, pp. 129– 136.
- “Imdb.” [Online]. Available: http://imdb.com
- K. Mouthami, K. N. Devi, and V. M. Bhaskaran, “Sentiment analysis and classification based on textual reviews,” in Information Communication and Embedded Systems (ICICES), 2013 International Conference on. IEEE, 2013, pp. 271–276.
- M. K. Jiawei Han, Data Mining:Concepts and Techniques. 500 Sansome Street, Suite 400, San Francisco, CA 94111: Diane Cerra, 2006.
- R. Yao and J. Chen, “Predicting movie sales revenue using online reviews.” in GrC, 2013, pp. 396–40