TL;DR
This study analyzes fear speech in Indian WhatsApp groups, revealing its characteristics, spread, and user engagement, highlighting challenges for detection and implications for offline violence prevention.
Contribution
First large-scale characterization and classification of fear speech in Indian WhatsApp groups, including dataset creation and analysis of its spread and user engagement.
Findings
Fear speech messages use symbols and events to create illusion of fear.
Current NLP models struggle to classify fear speech accurately.
Fear speech spreads faster and is less toxic than traditional hate speech.
Abstract
WhatsApp is the most popular messaging app in the world. Due to its popularity, WhatsApp has become a powerful and cheap tool for political campaigning being widely used during the 2019 Indian general election, where it was used to connect to the voters on a large scale. Along with the campaigning, there have been reports that WhatsApp has also become a breeding ground for harmful speech against various protected groups and religious minorities. Many such messages attempt to instil fear among the population about a specific (minority) community. According to research on inter-group conflict, such `fear speech' messages could have a lasting impact and might lead to real offline violence. In this paper, we perform the first large scale study on fear speech across thousands of public WhatsApp groups discussing politics in India. We curate a new dataset and try to characterize fear speech…
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