Towards Understanding the Role of Gender in Deploying Social Media-Based Mental Health Surveillance Models

Eli Sherman, Keith Harrigian, Carlos Aguirre, Mark Dredze

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spurred by advances in machine learning and natural language processing, developing social media-based mental health surveillance models has received substantial recent attention. For these models to be maximally useful, it is necessary to understand how they perform on various subgroups, especially those defined in terms of protected characteristics. In this paper we study the relationship between user demographics - focusing on gender - and depression. Considering a population of Reddit users with known genders and depression statuses, we analyze the degree to which depression predictions are subject to biases along gender lines using domaininformed classifiers. We then study our models' parameters to gain qualitative insight into the differences in posting behavior across genders.

Original languageEnglish (US)
Title of host publicationComputational Linguistics and Clinical Psychology
Subtitle of host publicationImproving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021
EditorsNazli Goharian, Philip Resnik, Andrew Yates, Molly Ireland, Kate Niederhoffer, Rebecca Resnik
PublisherAssociation for Computational Linguistics (ACL)
Pages217-223
Number of pages7
ISBN (Electronic)9781954085411
StatePublished - 2021
Event7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Virtual, Online
Duration: Jun 11 2021 → …

Publication series

NameComputational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021 - Proceedings of the 7th Workshop, in conjunction with NAACL 2021

Conference

Conference7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access, CLPsych 2021
CityVirtual, Online
Period6/11/21 → …

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Networks and Communications
  • Speech and Hearing

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