Sarcasm Detection of Media Text Using Deep Neural Networks

Author:

Ajnadkar Omkar

Publisher

Springer Singapore

Reference16 articles.

1. Sarcasm. American Heritage® Dictionary of the English Language, 5th edn. Houghton Mifflin Harcourt Publishing Company (2019)

2. Maynard, D., Greenwood, M.: Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014), pp. 4238–4243. Reykjavik, Iceland (2014). European Languages Resources Association (ELRA)

3. Riloff, E., Qadir, A., Surve, P., De Silva, L., Gilbert, N., Huang, R.: Sarcasm as contrast between a positive sentiment and negative situation. Proceedings of EMNLP, pp. 704–714 (2013)

4. Hajic, J., Tsujii, J. (eds.): COLING 2014. In: 25th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers. Dublin, Ireland. ACL (2014)

5. Joshi, A., Sharma, V., Bhattacharyya, P.: Harnessing context incongruity for sarcasm detection. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, vol. 2: Short Papers, pp. 757–762 (2015)

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