This paper explains the system developed for the Hate Speech Detection (HaSpeeDe) shared task within the 7th evaluation campaign EVALITA 2020 (Basile et al. 2020). The task solution proposed in this work is based on a fine-tuned BERT model. In cross-corpus evaluation, our model reached an F1 score of 77,56% on the tweets test set, and 60,31% on the news headlines test set.Questo articolo spiega il sistema sviluppato per il tesk finalizzato all’individuazione dei discorsi d’odio all’interno della campagna di valutazione EVALITA 2020 (Basile et al. 2020). La soluzione proposta per il task è basata su un raffinemento di un modello BERT. Nella valutazione finale il nostro modello raggiunge un valore F1 di 77,56% sul dataset di tweets e di 60,31...
The paper describes the Web platform built within the project “Contro l’Odio”, for monitoring and co...
International audienceEnglish. Despite the number of approaches recently proposed in NLP for detecti...
International audienceThe increasing popularity of social media platforms like Twitter and Facebook ...
Hate speech detection has become a crucial mission in many fields. This paper introduces the system ...
This report was written to describe the systems that were submitted by the team “TheNorth” for the H...
This report describes an approach to face a task regarding the identification of hate content and st...
International audienceThis paper reports on the systems the InriaFBK Team submitted to the EVALITA 2...
The task of identifying hate speech in social networks has recently attracted considerable interest ...
We describe in this paper the system submitted by the DH-FBK team to the HaSpeeDe evaluation task, a...
We describe the systems the RuG Team developed in the context of the Hate Speech Detection Task in I...
In this article, we present the results of applying a Stacking Ensemble method to the problem of hat...
We describe our approach to address Task A of the EVALITA 2020 Hate Speech Detection (HaSpeeDe2) cha...
The present paper describes two neural network systems used for Hate Speech Detection tasks that mak...
We describe in this paper the system submitted by the DH-FBK team to the HaSpeeDe evaluation task, a...
This paper describes the system that team YNU_OXZ submitted for EVALITA 2020. We participate in the ...
The paper describes the Web platform built within the project “Contro l’Odio”, for monitoring and co...
International audienceEnglish. Despite the number of approaches recently proposed in NLP for detecti...
International audienceThe increasing popularity of social media platforms like Twitter and Facebook ...
Hate speech detection has become a crucial mission in many fields. This paper introduces the system ...
This report was written to describe the systems that were submitted by the team “TheNorth” for the H...
This report describes an approach to face a task regarding the identification of hate content and st...
International audienceThis paper reports on the systems the InriaFBK Team submitted to the EVALITA 2...
The task of identifying hate speech in social networks has recently attracted considerable interest ...
We describe in this paper the system submitted by the DH-FBK team to the HaSpeeDe evaluation task, a...
We describe the systems the RuG Team developed in the context of the Hate Speech Detection Task in I...
In this article, we present the results of applying a Stacking Ensemble method to the problem of hat...
We describe our approach to address Task A of the EVALITA 2020 Hate Speech Detection (HaSpeeDe2) cha...
The present paper describes two neural network systems used for Hate Speech Detection tasks that mak...
We describe in this paper the system submitted by the DH-FBK team to the HaSpeeDe evaluation task, a...
This paper describes the system that team YNU_OXZ submitted for EVALITA 2020. We participate in the ...
The paper describes the Web platform built within the project “Contro l’Odio”, for monitoring and co...
International audienceEnglish. Despite the number of approaches recently proposed in NLP for detecti...
International audienceThe increasing popularity of social media platforms like Twitter and Facebook ...