Abstract
In this paper, we describe our submissions for PAN at CLEF 2021 contest. We tackled the subtask “Profiling Hate Speech Spreaders on Twitter”. We developed different models for English and Spanish languages, using classic machine learning methods like Support Vector Classifier, Multi-Layer Perceptron, Logistic Regression, Random Forest, Ada-Boost Classifier and K-Neighbors Classifier to more recent deep learning methods like BERT and Bidirectional LSTM.
| Original language | English |
|---|---|
| Pages (from-to) | 2178-2185 |
| Number of pages | 8 |
| Journal | CEUR Workshop Proceedings |
| Volume | 2936 |
| State | Published - 2021 |
| Event | 2021 Working Notes of CLEF - Conference and Labs of the Evaluation Forum, CLEF-WN 2021 - Virtual, Bucharest, Romania Duration: 21 Sep 2021 → 24 Sep 2021 |
Bibliographical note
Publisher Copyright:© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Keywords
- Ada-boost classifier
- Author profiling
- BERT
- English
- Hate speech
- LSTM
- Logistic regression
- MLP
- Random forest
- SVM
- Spanish