Working Paper No. 1350

Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity

Published: August 14, 2020Keywords: Online hate; Anonymity; Discussion forum; Machine learning; Big dataJEL-codes: C55; D00; D80; D90

Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity Emma von Essen and Joakim Jansson


In this paper, we quantify hateful content in online civic discussions of politics and estimate 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 hateful 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.


Reference:

von Essen, Emma and Joakim Jansson (2020), "Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity". IFN Working Paper No. 1350. Stockholm: The Research Institute of Industrial Economics (IFN). 

Interdisciplinary European Studies

The European Union and the Return of the Nation State

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This book explores the complex and ever-changing relationship between the European Union and its member states. The recent surge in tension in this relationship has been prompted by the actions of some member state governments as they question fundamental EU values and principles and refuse to implement common decisions seemingly on the basis of narrowly defined national interests.

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