An Interactive Exploratory Tool for the Task of Hate Speech Detection

Angelina McMillan-Major, Amandalynne Paullada, Yacine Jernite


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.
Anthology ID:
2022.hcinlp-1.2
Volume:
Proceedings of the Second Workshop on Bridging Human--Computer Interaction and Natural Language Processing
Month:
July
Year:
2022
Address:
Seattle, Washington
Editors:
Su Lin Blodgett, Hal Daumé III, Michael Madaio, Ani Nenkova, Brendan O'Connor, Hanna Wallach, Qian Yang
Venue:
HCINLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
11–20
Language:
URL:
https://aclanthology.org/2022.hcinlp-1.2
DOI:
10.18653/v1/2022.hcinlp-1.2
Bibkey:
Cite (ACL):
Angelina McMillan-Major, Amandalynne Paullada, and Yacine Jernite. 2022. An Interactive Exploratory Tool for the Task of Hate Speech Detection. In Proceedings of the Second Workshop on Bridging Human--Computer Interaction and Natural Language Processing, pages 11–20, Seattle, Washington. Association for Computational Linguistics.
Cite (Informal):
An Interactive Exploratory Tool for the Task of Hate Speech Detection (McMillan-Major et al., HCINLP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.hcinlp-1.2.pdf
Video:
 https://aclanthology.org/2022.hcinlp-1.2.mp4