Transformer-Based Approaches to Sentiment Detection-Reference-Cited by-同舟云学术

Transformer-Based Approaches to Sentiment Detection

Published:2023 Issue: Volume: Page:101-110
ISSN:1434-9922
Container-title:Recent Developments and the New Directions of Research, Foundations, and Applications
language:
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Author:

Ojo Olumide Ebenezer^ORCID,Ta Hoang Thang^ORCID,Gelbukh Alexander^ORCID,Calvo Hiram^ORCID,Adebanji Olaronke Oluwayemisi^ORCID,Sidorov Grigori^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-23476-7_10

Reference19 articles.

1. Congcong, W., Nulty, P., Lillis, D.: Transformer based Multi-task Learning for Disaster Tweet Categorisation CoRR, abs/2110.08010 (2021). https://arxiv.org/abs/2110.08010

2. Zhang, T., Schoene, A.M., Ananiadou, S.: Automatic identification of suicide notes with a transformer-based deep learning model Elsevier, vol. 25, pp. 100422, ISSN: 2214–7829 (2022). https://doi.org/10.1016/j.invent.2021.100422

3. Wang, Y., Zheng, J., Li, Q., Wang, C., Zhang, H., Gong, J.: XLNet-caps: personality classification from textual posts electronics. ISSN. 10(11), 2079–9292 (2021). https://doi.org/10.3390/electronics10111360

4. Dogra, v., Verma, S., Singh, A., Kavita, Talib, M.N., Humayun, M.: Banking news-events representation and classification with a novel hybrid model using DistilBERT and rule-based features Turkish J. Comput. Math. Educ. (TURCOMAT) 12(10), 3039–3054 (2021). https://doi.org/10.17762/turcomat.v12i10.4954

5. Ciniselli, M., Cooper, N., Pascarella, L., Poshyvanyk, D., Di Penta, M., Bavota, G.: An Empirical Study on the Usage of BERT Models for Code Completion CoRR, vol. abs/2103.07115 (2021). https://arxiv.org/abs/2103.07115