Misogynistic and xenophobic hate language online: a matter of anonymity

Emma von Essen () and Joakim Jansson
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Emma von Essen: Swedish Institute for Social Research, Stockholm University, Postal: SOFI, Stockholm University, SE-106 91 Stockholm, Sweden, https://www.sofi.su.se/

No 7/2020, Working Paper Series from Stockholm University, Swedish Institute for Social Research

Abstract: In this paper, we quantify hateful content in online civic discussions of politics and es- timate the causal link between hateful content and writer anonymity. To measure hate, we first develop a supervised machine-learning model that predicts hate against foreign residents and hate against women on a dominant Swedish Internet discussion forum. We find that an exogenous decrease in writer anonymity leads to less hate against foreign residents but an increase in hate against women. We conjecture that the mechanisms behind the changes comprise a combination of users decreasing the amount of their hate- ful writing and a substitution of hate against foreign residents for hate against women. The discussion of the results highlights the role of social repercussions in discouraging antisocial and criminal activities.

Keywords: online hate; anonymity; discussion forum; machine learning; big data (search for similar items in EconPapers)
JEL-codes: C55 D00 D80 D90 (search for similar items in EconPapers)
Pages: 77 pages
Date: 2020-08-20
New Economics Papers: this item is included in nep-big and nep-pay
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Related works:
Working Paper: Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:sofiwp:2020_007

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