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

2019/03/02 by Sara Moricz, Moricz, Sara
Computer Science · Health Professions · Social Sciences · #FOS: Economics and business #General Economics (econ.GN) #Hate Speech and Cyberbullying Detection #Media Influence and Politics #Migration, Refugees, and Integration #Names, Identity, and Discrimination Research #Romani and Gypsy Studies #Social Media and Politics

paper · pdf · doi:10.48550/arxiv.1903.00690

openalex publication_date 2019/03/02 · openalex created_date 2021/02/01 · openalex updated_date 2026/07/28

Abstract

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

Citations

• How Much Should We Trust Differences-In-Differences Estimates?
• The Economics of Cultural Transmission and the Dynamics of Preferences
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• Gender Identity and Relative Income within Households*
• A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks
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