Monitoring Suspicious Discussions on Social Media Case Study
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S.Somasundaran and J. Wiebe. Recognizing stances in ideological online debates. In workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pages 116-124. ACM,2010
Mostafa Karambeikar and Ali A. Ghorbani, Sentiment Analysis Of Social Issues. In 2012 International Conference on Social Informatics, pages 215-221. IEEE 2012
Nitin Indurkhya, Fred J. Damerau , Handbook of Natural Language Processing, Second Edition, CRC Press, 2010.
Ronen Feldman, James Sanger,The Text Mining Handbook-Advance Approaches in Analyzing Unstructured Data, Cambridge University Press,2007.
Jiawei Han, Micheline Kamber, Data Mining Concepts and Techniques, Morgan Kaufmann Publications, 2006. [5] Ronen Feldman, “Techniques and Application of Sentiment Analysis”, Communication of ACM, April 2013, vol. 56.No.4.
Ana C.E.S Lima and Leandro N.de Castro, “Automatic Sentiment Analysis of Twitter Messages”, IEEE Fourth International Conference on Computational Aspect .of Social Networks (CASoN), p.52-57, 2012.
Keisuke Mizumoto, Hidekazu Yanagimoto and Michifumi Yoshioka, “Sentiment Analysis of Stock Market News with Semi-supervised Learning”, IEEE Computer Society,IEEE/ACIS 11th International Conference on Computer and Information Science, p.325-328,2012.
Sang-Hyun Cho and Hang-Bong Kang, “Text Sentiment Classification for SNS-based Marketing Using Domain Sentiment Dictionary”, IEEE International Conference on Conference on consumer Electronics (ICCE), p.717-718, 2012.
Aurangzeb Khan and Baharum Baharudin, “Sentiment Classification Using Sentence-level Semantic Orientation of Opinion Terms form Blogs”, 2011.
Ms.K.Mouthami, Ms.K.Nirmala Devi, Dr.V.Murali Bhaskaran, “Sentiment Analysis and Classification Based on Textual Review”
DOI: https://doi.org/10.26483/ijarcs.v8i5.3297
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