An Effective Sarcasm Detection Approach Based on Sentimental Context and Individual Expression Habits-Reference-Cited by-同舟云学术

An Effective Sarcasm Detection Approach Based on Sentimental Context and Individual Expression Habits

Published:2021-01-22 Issue:1 Volume:14 Page:78-90
ISSN:1866-9956
Container-title:Cognitive Computation
language:en
Short-container-title:Cogn Comput

Author:

Du Yu,Li Tong^ORCID,Pathan Muhammad Salman,Teklehaimanot Hailay Kidu,Yang Zhen

Funder

Young Scientists Fund

Beijing Municipal Excellent Talents Foundation-Youth

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Link

https://link.springer.com/content/pdf/10.1007/s12559-021-09832-x.pdf

Reference39 articles.

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3. Amir S, Wallace BC, Lyu H, Carvalho P, Silva MJ. Modelling context with user embeddings for sarcasm detection in social media. In Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning; 2016. p. 167–177.

4. Ptáček T, Habernal I, Hong J. Sarcasm detection on czech and english twitter. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers; 2014. p. 213–223.

5. Bamman D, Smith NA. Contextualized sarcasm detection on twitter. In Ninth international AAAI conference on web and social media. Citeseer; 2015 p. 574–577.

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