Nipping in the Bud: Detection, Diffusion and Mitigation of Hate Speech
on Social Media
- URL: http://arxiv.org/abs/2201.00961v1
- Date: Tue, 4 Jan 2022 03:44:46 GMT
- Title: Nipping in the Bud: Detection, Diffusion and Mitigation of Hate Speech
on Social Media
- Authors: Tanmoy Chakraborty, Sarah Masud
- Abstract summary: This article presents methodological challenges that hinder building automated hate mitigation systems.
We discuss a series of our proposed solutions to limit the spread of hate speech on social media.
- Score: 21.47216483704825
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Since the proliferation of social media usage, hate speech has become a major
crisis. Hateful content can spread quickly and create an environment of
distress and hostility. Further, what can be considered hateful is contextual
and varies with time. While online hate speech reduces the ability of already
marginalised groups to participate in discussion freely, offline hate speech
leads to hate crimes and violence against individuals and communities. The
multifaceted nature of hate speech and its real-world impact have already
piqued the interest of the data mining and machine learning communities.
Despite our best efforts, hate speech remains an evasive issue for researchers
and practitioners alike. This article presents methodological challenges that
hinder building automated hate mitigation systems. These challenges inspired
our work in the broader area of combating hateful content on the web. We
discuss a series of our proposed solutions to limit the spread of hate speech
on social media.
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