使用双向长短期记忆网络对社交媒体上的少数群体压力披露进行分类。
Classifying Minority Stress Disclosure on Social Media with Bidirectional Long Short-Term Memory.
作者信息
Cascalheira Cory J, Hamdi Shah Muhammad, Scheer Jillian R, Saha Koustuv, Boubrahimi Soukaina Filali, De Choudhury Munmun
机构信息
New Mexico State University.
Syracuse University.
出版信息
Proc Int AAAI Conf Weblogs Soc Media. 2022 May 31;16:1373-1377.
Because of their stigmatized social status, sexual and gender minority (SGM; e.g., gay, transgender) people experience minority stress (i.e., identity-based stress arising from adverse social conditions). Given that minority stress is the leading framework for understanding health inequity among SGM people, researchers and clinicians need accurate methods to detect minority stress. Since social media fulfills important developmental, affiliative, and coping functions for SGM people, social media may be an ecologically valid channel for detecting minority stress. In this paper, we propose a bidirectional long short-term memory (BI-LSTM) network for classifying minority stress disclosed on Reddit. Our experiments on a dataset of 12,645 Reddit posts resulted in an average accuracy of 65%.
由于性取向和性别少数群体（SGM，例如同性恋者、跨性别者）的社会地位受到污名化，他们会经历少数群体压力（即由不利社会状况引发的基于身份认同的压力）。鉴于少数群体压力是理解SGM人群健康不平等问题的主要框架，研究人员和临床医生需要准确的方法来检测少数群体压力。由于社交媒体对SGM人群具有重要的发展、社交和应对功能，因此社交媒体可能是检测少数群体压力的一个生态有效渠道。在本文中，我们提出了一种双向长短期记忆（BI-LSTM）网络，用于对Reddit上披露的少数群体压力进行分类。我们在一个包含12645条Reddit帖子的数据集上进行的实验，平均准确率为65%。
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