This paper presents the different models submitted by the LT@Helsinki team for the SemEval2020 Shared Task 12. Our team participated in sub-tasks A and C; titled offensive language identification and offense target identification, respectively. In both cases we used the so called Bidirectional Encoder Representation from Transformer (BERT), a model pre-trained by Google and fine-tuned by us on the OLID dataset. The results show that offensive tweet classification is one of several language-based tasks where BERT can achieve state-of-the-art results.Peer reviewe
We present the second edition of the GermEval Shared Task on the Identification of Offensive Languag...
SemEval 2019 Task 6 was OffensEval: Identifying and Categorizing Offensive Language in Social Media....
Hate speech detection on social media platforms is crucial as it helps to avoid severe harm to margi...
This paper presents the different models submitted by the LT@Helsinki team for the SemEval2020 Share...
In this paper we present our submission to sub-task A at SemEval 2020 Task 12: Multilingual Offensiv...
We present the results and main findings of SemEval-2020 Task 12 on Multilingual Offensive Language ...
The popularity of social media platforms has led to an increase in user-generated content being post...
Abstract This paper presents the results and main findings of the HASOC-2021 Hate/Offensive Languag...
We introduce an approach to multilingual Offensive Language Detection based on the mBERT transformer...
As insulting statements become more frequent on online platforms, these negative statements create a...
This paper summarizes our group’s efforts in the offensive language identification shared task, whic...
In this paper, we describe the team BRUMS entry to OffensEval 2: Multilingual Offensive Language Ide...
In the past decade, usage of social media platforms has increased significantly. People use these pl...
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in Engl...
The paper describes the systems submitted to OffensEval (SemEval 2019, Task 6) on ‘Identifying and C...
We present the second edition of the GermEval Shared Task on the Identification of Offensive Languag...
SemEval 2019 Task 6 was OffensEval: Identifying and Categorizing Offensive Language in Social Media....
Hate speech detection on social media platforms is crucial as it helps to avoid severe harm to margi...
This paper presents the different models submitted by the LT@Helsinki team for the SemEval2020 Share...
In this paper we present our submission to sub-task A at SemEval 2020 Task 12: Multilingual Offensiv...
We present the results and main findings of SemEval-2020 Task 12 on Multilingual Offensive Language ...
The popularity of social media platforms has led to an increase in user-generated content being post...
Abstract This paper presents the results and main findings of the HASOC-2021 Hate/Offensive Languag...
We introduce an approach to multilingual Offensive Language Detection based on the mBERT transformer...
As insulting statements become more frequent on online platforms, these negative statements create a...
This paper summarizes our group’s efforts in the offensive language identification shared task, whic...
In this paper, we describe the team BRUMS entry to OffensEval 2: Multilingual Offensive Language Ide...
In the past decade, usage of social media platforms has increased significantly. People use these pl...
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in Engl...
The paper describes the systems submitted to OffensEval (SemEval 2019, Task 6) on ‘Identifying and C...
We present the second edition of the GermEval Shared Task on the Identification of Offensive Languag...
SemEval 2019 Task 6 was OffensEval: Identifying and Categorizing Offensive Language in Social Media....
Hate speech detection on social media platforms is crucial as it helps to avoid severe harm to margi...
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