Countering Online Hate Speech: An NLP Perspective
- URL: http://arxiv.org/abs/2109.02941v1
- Date: Tue, 7 Sep 2021 08:48:13 GMT
- Title: Countering Online Hate Speech: An NLP Perspective
- Authors: Mudit Chaudhary, Chandni Saxena, Helen Meng
- Abstract summary: Online toxicity - an umbrella term for online hateful behavior - manifests itself in forms such as online hate speech.
The rising mass communication through social media further exacerbates the harmful consequences of online hate speech.
This paper presents a holistic conceptual framework on hate-speech NLP countering methods along with a thorough survey on the current progress of NLP for countering online hate speech.
- Score: 34.19875714256597
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Online hate speech has caught everyone's attention from the news related to
the COVID-19 pandemic, US elections, and worldwide protests. Online toxicity -
an umbrella term for online hateful behavior, manifests itself in forms such as
online hate speech. Hate speech is a deliberate attack directed towards an
individual or a group motivated by the targeted entity's identity or opinions.
The rising mass communication through social media further exacerbates the
harmful consequences of online hate speech. While there has been significant
research on hate-speech identification using Natural Language Processing (NLP),
the work on utilizing NLP for prevention and intervention of online hate speech
lacks relatively. This paper presents a holistic conceptual framework on
hate-speech NLP countering methods along with a thorough survey on the current
progress of NLP for countering online hate speech. It classifies the countering
techniques based on their time of action, and identifies potential future
research areas on this topic.
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