research-article

Characterizing and predicting postpartum depression from shared facebook data

Authors:

Munmun De Choudhury,

Eric J. Horvitz,

Aaron HoffAuthors Info & Claims

CSCW '14: Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing

Pages 626 - 638

https://doi.org/10.1145/2531602.2531675

Published: 15 February 2014 Publication History

Abstract

The birth of a child is a major milestone in the life of parents. We leverage Facebook data shared voluntarily by 165 new mothers as streams of evidence for characterizing their postnatal experiences. We consider multiple measures including activity, social capital, emotion, and linguistic style in participants' Facebook data in pre- and postnatal periods. Our study includes detecting and predicting onset of post-partum depression (PPD). The work complements recent work on detecting and predicting significant postpartum changes in behavior, language, and affect from Twitter data. In contrast to prior studies, we gain access to ground truth on postpartum experiences via self-reports and a common psychometric instrument used to evaluate PPD. We develop a series of statistical models to predict, from data available before childbirth, a mother's likelihood of PPD. We corroborate our quantitative findings through interviews with mothers experiencing PPD. We find that increased social isolation and lowered availability of social capital on Facebook, are the best predictors of PPD in mothers.

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Alvarado Garcia AYang TMiceli M(2025)What Knowledge Do We Produce from Social Media Data and How?Proceedings of the ACM on Human-Computer Interaction10.1145/37012169:1(1-45)Online publication date: 10-Jan-2025
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Index Terms

Characterizing and predicting postpartum depression from shared facebook data
1. Human-centered computing
  1. Collaborative and social computing
  2. Human computer interaction (HCI)
2. Information systems
  1. Information retrieval
  2. Information storage systems

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cover image ACM Conferences

CSCW '14: Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing

February 2014

1600 pages

ISBN:9781450325400

DOI:10.1145/2531602

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Susan Fussell
Cornell University
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Microsoft Research
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Published: 15 February 2014

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https://dl.acm.org/doi/10.1145/3701217
Alvarado Garcia AYang TMiceli M(2025)What Knowledge Do We Produce from Social Media Data and How?Proceedings of the ACM on Human-Computer Interaction10.1145/37012169:1(1-45)Online publication date: 10-Jan-2025
https://dl.acm.org/doi/10.1145/3701216
Pavez JAllende H(2024)A Hybrid System Based on Bayesian Networks and Deep Learning for Explainable Mental Health DiagnosisApplied Sciences10.3390/app1418828314:18(8283)Online publication date: 14-Sep-2024
https://doi.org/10.3390/app14188283
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