@inproceedings{tawalbeh-etal-2020-saja,
title = "{SAJA} at {TRAC} 2020 Shared Task: Transfer Learning for Aggressive Identification with {XGB}oost",
author = "Tawalbeh, Saja and
Hammad, Mahmoud and
AL-Smadi, Mohammad",
editor = "Kumar, Ritesh and
Ojha, Atul Kr. and
Lahiri, Bornini and
Zampieri, Marcos and
Malmasi, Shervin and
Murdock, Vanessa and
Kadar, Daniel",
booktitle = "Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/2020.trac-1.16/",
pages = "99--105",
language = "eng",
ISBN = "979-10-95546-56-6",
abstract = "we have developed a system based on transfer learning technique depending on universal sentence encoder (USE) embedding that will be trained in our developed model using xgboost classifier to identify the aggressive text data from English content. A reference dataset has been provided from TRAC 2020 to evaluate the developed approach. The developed approach achieved in sub-task EN-A 60.75{\%} F1 (weighted) which ranked fourteenth out of sixteen teams and achieved 85.66{\%} F1 (weighted) in sub-task EN-B which ranked six out of fifteen teams."
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<abstract>we have developed a system based on transfer learning technique depending on universal sentence encoder (USE) embedding that will be trained in our developed model using xgboost classifier to identify the aggressive text data from English content. A reference dataset has been provided from TRAC 2020 to evaluate the developed approach. The developed approach achieved in sub-task EN-A 60.75% F1 (weighted) which ranked fourteenth out of sixteen teams and achieved 85.66% F1 (weighted) in sub-task EN-B which ranked six out of fifteen teams.</abstract>
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%0 Conference Proceedings
%T SAJA at TRAC 2020 Shared Task: Transfer Learning for Aggressive Identification with XGBoost
%A Tawalbeh, Saja
%A Hammad, Mahmoud
%A AL-Smadi, Mohammad
%Y Kumar, Ritesh
%Y Ojha, Atul Kr.
%Y Lahiri, Bornini
%Y Zampieri, Marcos
%Y Malmasi, Shervin
%Y Murdock, Vanessa
%Y Kadar, Daniel
%S Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying
%D 2020
%8 May
%I European Language Resources Association (ELRA)
%C Marseille, France
%@ 979-10-95546-56-6
%G eng
%F tawalbeh-etal-2020-saja
%X we have developed a system based on transfer learning technique depending on universal sentence encoder (USE) embedding that will be trained in our developed model using xgboost classifier to identify the aggressive text data from English content. A reference dataset has been provided from TRAC 2020 to evaluate the developed approach. The developed approach achieved in sub-task EN-A 60.75% F1 (weighted) which ranked fourteenth out of sixteen teams and achieved 85.66% F1 (weighted) in sub-task EN-B which ranked six out of fifteen teams.
%U https://aclanthology.org/2020.trac-1.16/
%P 99-105
Markdown (Informal)
[SAJA at TRAC 2020 Shared Task: Transfer Learning for Aggressive Identification with XGBoost](https://aclanthology.org/2020.trac-1.16/) (Tawalbeh et al., TRAC 2020)
ACL