The increasing influence from users in social media has made that aggressive content disseminates over the internet. To tackle this problem, recent advances in Aggressive Language Detection have demonstrated a good performance of Deep Learning techniques. Recently Transformer based architectures such as Bidirectional Encoder Representations from Transformer (BERT) outperformed previous aggressive text detection baselines. However, most of the Transformers-based approaches are unable to properly capture global information such as language vocabulary. Thus, in this work, we focus on aggressive content detection using the combination of Vocabulary Graph Convolutional Network (VGCN) to capture global information and BERT to model local information. This combined approach called VGCN-BERT allows us to improve the feature level representation in Spanish aggressive language detection. Our experiments were performed on a benchmark called MEX-A3T aggressiveness dataset which is composed of aggressive and non-aggressive Tweets written in the Mexican Spanish variant. We report 86.46\% in terms of F1-score using this VGCN-BERT approach which allows us to obtain comparable results with the current state-of-the-art, ensemble BERT, so as to detect aggressive content regarding the track MEX-A3T 2020.

Aggressive Language Detection using VGCN-BERT for Spanish Texts


**Chairs:** Diego Furtado Silva, Karina Valdivia and Andre Britto


Text Mining and Natural Language Processing I

technical paper

**BRACIS** originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – **SBIA** (22 editions), and the Brazilian Symposium on Neural Networks – **SBRN** (13 editions). **ENIAC** is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. **STIL** is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: **CE-IA**, **CE-IC** and **CE-PLN**.

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BRACIS 2021

BRACIS originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – SBIA (22 editions), and the Brazilian Symposium on Neural Networks – SBRN (13 editions). 
ENIAC is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. 
STIL is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: CE-IA, CE-IC and CE-PLN

Errol Mamani

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Aggressive Language Detection using VGCN-BERT for Spanish Texts

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