@inproceedings{pilankar-etal-2022-detecting,
title = "Detecting Violation of Human Rights via Social Media",
author = "Pilankar, Yash and
Haque, Rejwanul and
Hasanuzzaman, Mohammed and
Stynes, Paul and
Pathak, Pramod",
editor = "Wan, Mingyu and
Huang, Chu-Ren",
booktitle = "Proceedings of the First Computing Social Responsibility Workshop within the 13th Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.csrnlp-1.6",
pages = "40--45",
abstract = "Social media is not just meant for entertainment, it provides platforms for sharing information, news, facts and events. In the digital age, activists and numerous users are seen to be vocal regarding human rights and their violations in social media. However, their voices do not often reach to the targeted audience and concerned human rights organization. In this work, we aimed at detecting factual posts in social media about violation of human rights in any part of the world. The end product of this research can be seen as an useful asset for different peacekeeping organizations who could exploit it to monitor real-time circumstances about any incident in relation to violation of human rights. We chose one of the popular micro-blogging websites, Twitter, for our investigation. We used supervised learning algorithms in order to build human rights violation identification (HRVI) models which are able to identify Tweets in relation to incidents of human right violation. For this, we had to manually create a data set, which is one of the contributions of this research. We found that our classification models that were trained on this gold-standard dataset performed excellently in classifying factual Tweets about human rights violation, achieving an accuracy of upto 93{\%} on hold-out test set.",
}
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<abstract>Social media is not just meant for entertainment, it provides platforms for sharing information, news, facts and events. In the digital age, activists and numerous users are seen to be vocal regarding human rights and their violations in social media. However, their voices do not often reach to the targeted audience and concerned human rights organization. In this work, we aimed at detecting factual posts in social media about violation of human rights in any part of the world. The end product of this research can be seen as an useful asset for different peacekeeping organizations who could exploit it to monitor real-time circumstances about any incident in relation to violation of human rights. We chose one of the popular micro-blogging websites, Twitter, for our investigation. We used supervised learning algorithms in order to build human rights violation identification (HRVI) models which are able to identify Tweets in relation to incidents of human right violation. For this, we had to manually create a data set, which is one of the contributions of this research. We found that our classification models that were trained on this gold-standard dataset performed excellently in classifying factual Tweets about human rights violation, achieving an accuracy of upto 93% on hold-out test set.</abstract>
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%0 Conference Proceedings
%T Detecting Violation of Human Rights via Social Media
%A Pilankar, Yash
%A Haque, Rejwanul
%A Hasanuzzaman, Mohammed
%A Stynes, Paul
%A Pathak, Pramod
%Y Wan, Mingyu
%Y Huang, Chu-Ren
%S Proceedings of the First Computing Social Responsibility Workshop within the 13th Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F pilankar-etal-2022-detecting
%X Social media is not just meant for entertainment, it provides platforms for sharing information, news, facts and events. In the digital age, activists and numerous users are seen to be vocal regarding human rights and their violations in social media. However, their voices do not often reach to the targeted audience and concerned human rights organization. In this work, we aimed at detecting factual posts in social media about violation of human rights in any part of the world. The end product of this research can be seen as an useful asset for different peacekeeping organizations who could exploit it to monitor real-time circumstances about any incident in relation to violation of human rights. We chose one of the popular micro-blogging websites, Twitter, for our investigation. We used supervised learning algorithms in order to build human rights violation identification (HRVI) models which are able to identify Tweets in relation to incidents of human right violation. For this, we had to manually create a data set, which is one of the contributions of this research. We found that our classification models that were trained on this gold-standard dataset performed excellently in classifying factual Tweets about human rights violation, achieving an accuracy of upto 93% on hold-out test set.
%U https://aclanthology.org/2022.csrnlp-1.6
%P 40-45
Markdown (Informal)
[Detecting Violation of Human Rights via Social Media](https://aclanthology.org/2022.csrnlp-1.6) (Pilankar et al., CSRNLP 2022)
ACL
- Yash Pilankar, Rejwanul Haque, Mohammed Hasanuzzaman, Paul Stynes, and Pramod Pathak. 2022. Detecting Violation of Human Rights via Social Media. In Proceedings of the First Computing Social Responsibility Workshop within the 13th Language Resources and Evaluation Conference, pages 40–45, Marseille, France. European Language Resources Association.