Impact and dynamics of hate and counter speech online
Santa Fe Institute, 1399 Hyde Park Road, 87501, Santa Fe, NM, USA
2 Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, 04103, Leipzig, Germany
3 Department of Computer Science and Vermont Complex Systems Center, University of Vermont, 05405, Burlington, VT, USA
4 Complexity Science Hub Vienna, Josefstädter Straße 39, 1080, Vienna, Austria
5 Vermont Complex Systems Center, University of Vermont, 05405, Burlington, VT, USA
Accepted: 21 December 2021
Published online: 24 January 2022
Citizen-generated counter speech is a promising way to fight hate speech and promote peaceful, non-polarized discourse. However, there is a lack of large-scale longitudinal studies of its effectiveness for reducing hate speech. To this end, we perform an exploratory analysis of the effectiveness of counter speech using several different macro- and micro-level measures to analyze 131,366 political conversations that took place on German Twitter over four years. We report on the dynamic interactions of hate and counter speech over time and provide insights into whether, as in ‘classic’ bullying situations, organized efforts are more effective than independent individuals in steering online discourse. Taken together, our results build a multifaceted picture of the dynamics of hate and counter speech online. While we make no causal claims due to the complexity of discourse dynamics, our findings suggest that organized hate speech is associated with changes in public discourse and that counter speech—especially when organized—may help curb hateful rhetoric in online discourse.
Key words: Hate speech / Counter speech / Twitter / Natural language processing / Time-series analysis
© The Author(s) 2022. corrected publication 2023
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