@inproceedings{hassan-etal-2020-alt,
title = "{ALT} Submission for {OSACT} Shared Task on Offensive Language Detection",
author = "Hassan, Sabit and
Samih, Younes and
Mubarak, Hamdy and
Abdelali, Ahmed and
Rashed, Ammar and
Chowdhury, Shammur Absar",
editor = "Al-Khalifa, Hend and
Magdy, Walid and
Darwish, Kareem and
Elsayed, Tamer and
Mubarak, Hamdy",
booktitle = "Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resource Association",
url = "https://aclanthology.org/2020.osact-1.9",
pages = "61--65",
abstract = "In this paper, we describe our efforts at OSACT Shared Task on Offensive Language Detection. The shared task consists of two subtasks: offensive language detection (Subtask A) and hate speech detection (Subtask B). For offensive language detection, a system combination of Support Vector Machines (SVMs) and Deep Neural Networks (DNNs) achieved the best results on development set, which ranked 1st in the official results for Subtask A with F1-score of 90.51{\%} on the test set. For hate speech detection, DNNs were less effective and a system combination of multiple SVMs with different parameters achieved the best results on development set, which ranked 4th in official results for Subtask B with F1-macro score of 80.63{\%} on the test set.",
language = "English",
ISBN = "979-10-95546-51-1",
}
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%0 Conference Proceedings
%T ALT Submission for OSACT Shared Task on Offensive Language Detection
%A Hassan, Sabit
%A Samih, Younes
%A Mubarak, Hamdy
%A Abdelali, Ahmed
%A Rashed, Ammar
%A Chowdhury, Shammur Absar
%Y Al-Khalifa, Hend
%Y Magdy, Walid
%Y Darwish, Kareem
%Y Elsayed, Tamer
%Y Mubarak, Hamdy
%S Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection
%D 2020
%8 May
%I European Language Resource Association
%C Marseille, France
%@ 979-10-95546-51-1
%G English
%F hassan-etal-2020-alt
%X In this paper, we describe our efforts at OSACT Shared Task on Offensive Language Detection. The shared task consists of two subtasks: offensive language detection (Subtask A) and hate speech detection (Subtask B). For offensive language detection, a system combination of Support Vector Machines (SVMs) and Deep Neural Networks (DNNs) achieved the best results on development set, which ranked 1st in the official results for Subtask A with F1-score of 90.51% on the test set. For hate speech detection, DNNs were less effective and a system combination of multiple SVMs with different parameters achieved the best results on development set, which ranked 4th in official results for Subtask B with F1-macro score of 80.63% on the test set.
%U https://aclanthology.org/2020.osact-1.9
%P 61-65
Markdown (Informal)
[ALT Submission for OSACT Shared Task on Offensive Language Detection](https://aclanthology.org/2020.osact-1.9) (Hassan et al., OSACT 2020)
ACL
- Sabit Hassan, Younes Samih, Hamdy Mubarak, Ahmed Abdelali, Ammar Rashed, and Shammur Absar Chowdhury. 2020. ALT Submission for OSACT Shared Task on Offensive Language Detection. In Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection, pages 61–65, Marseille, France. European Language Resource Association.