@inproceedings{das-etal-2023-team,
title = "Team Error Point at {BLP}-2023 Task 1: A Comprehensive Approach for Violence Inciting Text Detection using Deep Learning and Traditional Machine Learning Algorithm",
author = "Das, Rajesh and
Maowa, Jannatul and
Ajmain, Moshfiqur and
Yeiad, Kabid and
Islam, Mirajul and
Khushbu, Sharun",
editor = "Alam, Firoj and
Kar, Sudipta and
Chowdhury, Shammur Absar and
Sadeque, Farig and
Amin, Ruhul",
booktitle = "Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.banglalp-1.30",
doi = "10.18653/v1/2023.banglalp-1.30",
pages = "236--240",
abstract = "In the modern digital landscape, social media platforms have the dual role of fostering unprecedented connectivity and harboring a dark underbelly in the form of widespread violence-inciting content. Pioneering research in Bengali social media aims to provide a groundbreaking solution to this issue. This study thoroughly investigates violence-inciting text classification using a diverse range of machine learning and deep learning models, offering insights into content moderation and strategies for enhancing online safety. Situated at the intersection of technology and social responsibility, the aim is to empower platforms and communities to combat online violence. By providing insights into model selection and methodology, this work makes a significant contribution to the ongoing dialogue about the challenges posed by the darker aspects of the digital era. Our system scored 31.913 and ranked 26 among the participants.",
}
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%0 Conference Proceedings
%T Team Error Point at BLP-2023 Task 1: A Comprehensive Approach for Violence Inciting Text Detection using Deep Learning and Traditional Machine Learning Algorithm
%A Das, Rajesh
%A Maowa, Jannatul
%A Ajmain, Moshfiqur
%A Yeiad, Kabid
%A Islam, Mirajul
%A Khushbu, Sharun
%Y Alam, Firoj
%Y Kar, Sudipta
%Y Chowdhury, Shammur Absar
%Y Sadeque, Farig
%Y Amin, Ruhul
%S Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F das-etal-2023-team
%X In the modern digital landscape, social media platforms have the dual role of fostering unprecedented connectivity and harboring a dark underbelly in the form of widespread violence-inciting content. Pioneering research in Bengali social media aims to provide a groundbreaking solution to this issue. This study thoroughly investigates violence-inciting text classification using a diverse range of machine learning and deep learning models, offering insights into content moderation and strategies for enhancing online safety. Situated at the intersection of technology and social responsibility, the aim is to empower platforms and communities to combat online violence. By providing insights into model selection and methodology, this work makes a significant contribution to the ongoing dialogue about the challenges posed by the darker aspects of the digital era. Our system scored 31.913 and ranked 26 among the participants.
%R 10.18653/v1/2023.banglalp-1.30
%U https://aclanthology.org/2023.banglalp-1.30
%U https://doi.org/10.18653/v1/2023.banglalp-1.30
%P 236-240
Markdown (Informal)
[Team Error Point at BLP-2023 Task 1: A Comprehensive Approach for Violence Inciting Text Detection using Deep Learning and Traditional Machine Learning Algorithm](https://aclanthology.org/2023.banglalp-1.30) (Das et al., BanglaLP 2023)
ACL