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Using Artificial Intelligence to Recapture Norms: Did #metoo change gender norms in Sweden?

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  • Sara Moricz

Abstract

Norms are challenging to define and measure, but this paper takes advantage of text data and the recent development in machine learning to create an encompassing measure of norms. An LSTM neural network is trained to detect gendered language. The network functions as a tool to create a measure on how gender norms changes in relation to the Metoo movement on Swedish Twitter. This paper shows that gender norms on average are less salient half a year after the date of the first appearance of the hashtag #Metoo. Previous literature suggests that gender norms change over generations, but the current result suggests that norms can change in the short run.

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  • Sara Moricz, 2019. "Using Artificial Intelligence to Recapture Norms: Did #metoo change gender norms in Sweden?," Papers 1903.00690, arXiv.org.
    • Handle: RePEc:arx:papers:1903.00690
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    Cited by:

    1. Henrika Langen, 2022. "The Impact of the #MeToo Movement on Language at Court -- A text-based causal inference approach," Papers 2209.00409, arXiv.org, revised Sep 2023.

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