Abstract
This paper describes the approach of team CENTamil used for abusive comment detection in Tamil. This task aims to identify whether a given comment contains abusive comments. We used TF-IDF with char-wb analyzers with Random Kitchen Sink (RKS) algorithm to create feature vectors and the Support Vector Machine (SVM) classifier with polynomial kernel for classification. We used this method for both Tamil and Tamil-English datasets and secured first place with an f1-score of 0.32 and seventh place with an f1-score of 0.25, respectively. The code for our approach is shared in the GitHub repository.
Cite
CITATION STYLE
Prasanth, S. N., Raj, R. A., Adhithan, P., Premjith, B., & Soman, K. P. (2022). CEN-Tamil@DravidianLangTech-ACL2022: Abusive Comment detection in Tamil using TF-IDF and Random Kitchen Sink Algorithm. In DravidianLangTech 2022 - 2nd Workshop on Speech and Language Technologies for Dravidian Languages, Proceedings of the Workshop (pp. 70–74). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.dravidianlangtech-1.11
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