Vicomtech at DA-VINCIS: Detection of Aggressive and Violent Incidents from Social Media in Spanish

Date: 20.09.2022


Abstract

This paper describes the participation of the Vicomtech NLP team in the DA-VINCIS shared task. This shared task is focused on mentions of violent events in Spanish tweets, and proposes two subtasks: first, detecting whether a violent incident is mentioned in a tweet; and, second, determining which type of violent event is being mentioned. We participated in this shared task with multiple systems built on Transformer-based models, which we fine-tuned on different versions of the provided data. Among others, we explored the impact of automatic data augmentation and relabelling. Further, we tested masking keywords during training as a means to avoid the models from overfitting these recurrent expressions. Our systems ranked in 2nd place in both tasks, with F1-scores of 77.32 and 52.86 respectively.

BIB_text

@Article {
title = {Vicomtech at DA-VINCIS: Detection of Aggressive and Violent Incidents from Social Media in Spanish},
keywds = {
Deep Learning, Transformers, Text Classification, Spanish, Online Social Networks
}
abstract = {

This paper describes the participation of the Vicomtech NLP team in the DA-VINCIS shared task. This shared task is focused on mentions of violent events in Spanish tweets, and proposes two subtasks: first, detecting whether a violent incident is mentioned in a tweet; and, second, determining which type of violent event is being mentioned. We participated in this shared task with multiple systems built on Transformer-based models, which we fine-tuned on different versions of the provided data. Among others, we explored the impact of automatic data augmentation and relabelling. Further, we tested masking keywords during training as a means to avoid the models from overfitting these recurrent expressions. Our systems ranked in 2nd place in both tasks, with F1-scores of 77.32 and 52.86 respectively.


}
date = {2022-09-20},
}
Vicomtech

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48014 Bilbao (Spain)

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