英文标题：
《Using Artificial Intelligence to Recapture Norms: Did #metoo change
  gender norms in Sweden?》
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作者：
Sara Moricz
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最新提交年份：
2019
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英文摘要：
  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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中文摘要：
规范的定义和度量很有挑战性，但本文利用文本数据和机器学习的最新发展来创建一个全面的规范度量。训练一个LSTM神经网络来检测性别语言。该网络的功能是作为一种工具，在瑞典推特上创建一个衡量性别规范如何与Metoo运动相关的变化的工具。这篇论文表明，在标签“我”首次出现的半年后，性别规范的平均水平就不那么显著了。以前的文献表明，性别规范会随着时代的推移而改变，但目前的结果表明，规范在短期内可能会改变。
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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