TY - GEN
T1 - Hate Speech Recognition in Chilean Tweets
AU - Tobar-Arancibia, Alfonso
AU - Moreno, Sebastian
AU - Lopatin, Javier
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Hate speech, which targets specific groups based on race, religion, or sexual orientation, is a growing concern, especially on social media. Detecting hate speech is a critical research area, but most models are developed in English, leaving a gap for other languages like Spanish. Spanish presents additional challenges due to its regional variants and slang. In this paper, we introduce HateStack, the winning model of the 2022 Datathon at Universidad Técnica Federico Santa Maria, Chile, designed to detect hate speech in Chilean tweets. HateStack is a two-level ensemble model comprising a feature extraction process, five Level-l models, and a logistic regression as a second-level model. The results demonstrate that HateStack outperforms other ensemble models and RoBERTuito, a transformer-based deep learning model tailored for hate speech detection on tweets. Developing such models in non-English languages is important to detect hate speech effectively.
AB - Hate speech, which targets specific groups based on race, religion, or sexual orientation, is a growing concern, especially on social media. Detecting hate speech is a critical research area, but most models are developed in English, leaving a gap for other languages like Spanish. Spanish presents additional challenges due to its regional variants and slang. In this paper, we introduce HateStack, the winning model of the 2022 Datathon at Universidad Técnica Federico Santa Maria, Chile, designed to detect hate speech in Chilean tweets. HateStack is a two-level ensemble model comprising a feature extraction process, five Level-l models, and a logistic regression as a second-level model. The results demonstrate that HateStack outperforms other ensemble models and RoBERTuito, a transformer-based deep learning model tailored for hate speech detection on tweets. Developing such models in non-English languages is important to detect hate speech effectively.
KW - Deep Learning
KW - Ensemble Models
KW - Hate Speech
KW - Machine Learning
KW - Stacking
UR - http://www.scopus.com/inward/record.url?scp=85178999475&partnerID=8YFLogxK
U2 - 10.1109/SCCC59417.2023.10315748
DO - 10.1109/SCCC59417.2023.10315748
M3 - Conference contribution
AN - SCOPUS:85178999475
T3 - Proceedings - International Conference of the Chilean Computer Science Society, SCCC
BT - 2023 42nd IEEE International Conference of the Chilean Computer Science Society, SCCC 2023
PB - IEEE Computer Society
T2 - 42nd IEEE International Conference of the Chilean Computer Science Society, SCCC 2023
Y2 - 23 October 2023 through 26 October 2023
ER -