Author:
Adebanji Olaronke Oluwayemisi,Gelbukh Irina,Calvo Hiram,Ojo Olumide Ebenezer
Publisher
Springer Nature Switzerland
Reference20 articles.
1. Aroyehun, S.T., Gelbukh, A.: Aggression detection in social media: using deep neural networks, data augmentation, and pseudo labeling. In: Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pp. 90–97. Association for Computational Linguistics, Santa Fe, New Mexico, USA, August 2018
2. Aroyehun, S.T., Gelbukh, A.: Detection of adverse drug reaction in tweets using a combination of heterogeneous word embeddings. In: Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task, pp. 133–135. Association for Computational Linguistics, Florence, Italy, August 2019. https://doi.org/10.18653/v1/W19-3224, https://aclanthology.org/W19-3224
3. Ashraf, N., Mustafa, R., Sidorov, G., Gelbukh, A.F.: Individual vs. group violent threats classification in online discussions. In: Companion of The 2020 Web Conference 2020, Taipei, Taiwan, 20–24 April 2020, pp. 629–633. ACM/IW3C2 (2020). https://doi.org/10.1145/3366424.3385778
4. Clarke, I., Grieve, J.: Stylistic variation on the Donald Trump twitter account: a linguistic analysis of tweets posted between 2009 and 2018. PLOS ONE 14, 1–27 (2019). https://doi.org/10.1371/journal.pone.0222062
5. Go, A., Bhayani, R., Huang, L.: Twitter sentiment classification using distant supervision. Processing 1–6 (2009)
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