@inproceedings{mcmillan-major-etal-2022-interactive,
title = "An Interactive Exploratory Tool for the Task of Hate Speech Detection",
author = "McMillan-Major, Angelina and
Paullada, Amandalynne and
Jernite, Yacine",
editor = "Blodgett, Su Lin and
Daum{\'e} III, Hal and
Madaio, Michael and
Nenkova, Ani and
O'Connor, Brendan and
Wallach, Hanna and
Yang, Qian",
booktitle = "Proceedings of the Second Workshop on Bridging Human--Computer Interaction and Natural Language Processing",
month = jul,
year = "2022",
address = "Seattle, Washington",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.hcinlp-1.2/",
doi = "10.18653/v1/2022.hcinlp-1.2",
pages = "11--20",
abstract = "With the growth of Automatic Content Moderation (ACM) on widely used social media platforms, transparency into the design of moderation technology and policy is necessary for online communities to advocate for themselves when harms occur. In this work, we describe a suite of interactive modules to support the exploration of various aspects of this technology, and particularly of those components that rely on English models and datasets for hate speech detection, a subtask within ACM. We intend for this demo to support the various stakeholders of ACM in investigating the definitions and decisions that underpin current technologies such that those with technical knowledge and those with contextual knowledge may both better understand existing systems."
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%0 Conference Proceedings
%T An Interactive Exploratory Tool for the Task of Hate Speech Detection
%A McMillan-Major, Angelina
%A Paullada, Amandalynne
%A Jernite, Yacine
%Y Blodgett, Su Lin
%Y Daumé III, Hal
%Y Madaio, Michael
%Y Nenkova, Ani
%Y O’Connor, Brendan
%Y Wallach, Hanna
%Y Yang, Qian
%S Proceedings of the Second Workshop on Bridging Human–Computer Interaction and Natural Language Processing
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, Washington
%F mcmillan-major-etal-2022-interactive
%X With the growth of Automatic Content Moderation (ACM) on widely used social media platforms, transparency into the design of moderation technology and policy is necessary for online communities to advocate for themselves when harms occur. In this work, we describe a suite of interactive modules to support the exploration of various aspects of this technology, and particularly of those components that rely on English models and datasets for hate speech detection, a subtask within ACM. We intend for this demo to support the various stakeholders of ACM in investigating the definitions and decisions that underpin current technologies such that those with technical knowledge and those with contextual knowledge may both better understand existing systems.
%R 10.18653/v1/2022.hcinlp-1.2
%U https://aclanthology.org/2022.hcinlp-1.2/
%U https://doi.org/10.18653/v1/2022.hcinlp-1.2
%P 11-20
Markdown (Informal)
[An Interactive Exploratory Tool for the Task of Hate Speech Detection](https://aclanthology.org/2022.hcinlp-1.2/) (McMillan-Major et al., HCINLP 2022)
ACL