Baby steps: evaluation of a system to support record-keeping for parents of young children
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What do people ask their social networks, and why?: a survey study of status message q&a behavior
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Social capital on facebook: differentiating uses and users
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
MammiBelli: sharing baby activity levels between expectant mothers and their intimate social groups
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Who wants to know?: question-asking and answering practices among facebook users
Proceedings of the 2013 conference on Computer supported cooperative work
Major life changes and behavioral markers in social media: case of childbirth
Proceedings of the 2013 conference on Computer supported cooperative work
Predicting postpartum changes in emotion and behavior via social media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Digital motherhood: how does technology help new mothers?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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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.