A Comprehensive study: - Sarcasm detection in sentimental analysis
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Sarcasm detection is one of the active research area in sentimental analysis. However this paper talks about one of the recent issue in sentimental analysis that us sarcasm detection. In our work, we have described different techniques used in sarcasm detection that helps a novice researcher in efficient way. This paper represent different methodologies of carrying out research in this field.
-  Ashwin Rajadesingan, Reza Zafarani, and Huan Liu, Sarcasm detection on twitter: A behavioural modeling approach. Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, ACM, 2015.
-  Santosh Kumar Bharti, Korra Sathya Babu, and Sanjay Kumar Jena, “Parsing-based sarcasm sentiment recognition in Twitter data. 2015IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2015.
-  Mondher Bouazizi and Tomoaki Otsuki. A pattern-based approach for sarcasm detection on twitter. IEEE Transl. 2016.
-  T. Mikolov, K. Chen, G. Corrado, and J. Dean, Efficient estimation of word representations in vector space. Proc. Int. Conf. Learning Representations, 2013. arXiv:1301.3781
-  F. Morin and Y. Bengio, “Hierarchical probabilistic neural network language model. Proc. Int. Workshop Artif. Intell. Statist. 2005, pp. 246–252.
-  S. K. Bharti, K. S. Babuve S. K. Jena, Parsing-based Sarcasm Sentiment Recognition in Twitter Data. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Paris, 2015.
-  Mondher Bouazizi, Tomoaki Ohtsuki, Sarcasm Detection in Twitter. Global Communications Conference (GLOBECOM), 2015 IEEE.
-  Setra Genyang Wicana, Taha Yasin İbisoglu, Uraz Yavanoglu, A Review on Sarcasm Detection from Machine-Learning Perspective. 2017 IEEE 11th International Conference on Semantic Computing
-  D.Davidov, Dmitry, O. Tsur, A. Rappoport. Semisupervised Recognition of Sarcastic sentences in Twitter and Amazon. Proc. 14th Conf. on Computational Natural Language Learning, pp. 107116, 2010
-  Shweta Rana, Archana Singh, Comparative analysis of sentiment orientation using SVM and Naive Bayes techniques. 2nd International Conference on Next Generation Computing Technologies (NGCT) 2016
-  B. Joyce and J. Deng, Sentiment analysis of tweets for the 2016 US presidential election. 2017 IEEE MIT Undergraduate Research Technology Conference (URTC), 2017, pp. 1-4, doi: 10.1109/URTC.2017.8284176
-  Bamman, David, and Noah A. Smith. Contextualized Sarcasm Detection on Twitter. Ninth International AAAI Conference on Web and Social Media. 2015
-  A. K. Soni, Multi-lingual sentiment analysis of Twitter data by using classification algorithms. 2017 Second International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2017, pp. 1-5, doi: 10.1109/ICECCT.2017.8117884
-  Aditya Joshi, Vaibhav Tripathi, Pushpak Bhattacharyya, Mark Carman, “Harnessing Sequence Labeling for Sarcasm Detection in Dialogue from TV Series ‘Friends’ “Conference on Computational Natural Language Learning (CoNLL), pages 146–155, Berlin, Germany, August 7-12, 2016.
-  K. S. Krishnaveni, R. R. Pai and V. Iyer, Faculty rating system based on student feedbacks using sentimental analysis. 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017, pp. 1648-1653, doi: 10.1109/ICACCI.2017.8126079
-  Lohita Sivaprakasam, Aarthe Jayaprakash, A Study on Sarcasm Detection Algorithms, International Journal of Engineering Technology Science and Research Volume 4, Issue 9 September 2017
-  Han-Xiaoshi, Xiao-Junli, A sentiment analysis model for hotel reviews based on supervised learning, International Conference on Machine Learning and Cybernetics, Guilin, 10-13 July, 2011
-  Aditya Joshi, Vinita Sharma, Pushpak Bhattacharyya, Harnessing context incongruity for sarcasm detection, 7th International Joint Conference on Natural Language Processing, Vol. 2. 757-762
-  Magistry, P., Hsieh, SK. & Chang, YY. Sentiment detection in micro-blogs using unsupervised chunk extraction. Lingua Sinica 2, 1 (2016). https://doi.org/10.1186/s40655-015-0010-8
-  M. Korakakis, E. Spyrou and P. Mylonas, A survey on political event analysis in Twitter. 2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP), 2017, pp. 14-19, doi: 10.1109/SMAP.2017.8022660
-  Duyu Tang, Furu Wei, Bing Qin, Nan Yang, Ting Liu, and Ming Zhou, Sentiment Embeddings with Applications to Sentiment Analysis, IEEE Transactions on Knowledge and Data Engineering, Vol. 28, no. 2, February 2016
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