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Accepted for/Published in: JMIR Pediatrics and Parenting

Date Submitted: Sep 30, 2018
Open Peer Review Period: Oct 6, 2018 - Oct 23, 2018
Date Accepted: Nov 9, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Exploring the Transition to Fatherhood: Feasibility Study Using Social Media and Machine Learning

Teague SJ, Shatte AB

Exploring the Transition to Fatherhood: Feasibility Study Using Social Media and Machine Learning

JMIR Pediatr Parent 2018;1(2):e12371

DOI: 10.2196/12371

PMID: 31518298

PMCID: 6715057

Exploring the Transition to Fatherhood: Feasibility Study Using Social Media and Machine Learning

  • Samantha J Teague; 
  • Adrian BR Shatte

ABSTRACT

Background:

Fathers’ experiences across the transition to parenthood are underreported in the literature. Social media offers the potential to capture fathers’ experiences in real time and at scale while also removing the barriers that fathers typically face in participating in research and clinical care.

Objective:

This study aimed to assess the feasibility of using social media data to map the discussion topics of fathers across the fatherhood transition.

Methods:

Discussion threads from two Web-based parenting communities, r/Daddit and r/PreDaddit from the social media platform Reddit, were collected over a 2-week period, resulting in 1980 discussion threads contributed to by 5853 unique users. An unsupervised machine learning algorithm was then implemented to group discussion threads into topics within each community and across a combined collection of all discussion threads.

Results:

Results demonstrated that men use Web-based communities to share the joys and challenges of the fatherhood experience. Minimal overlap in discussions was found between the 2 communities, indicating that distinct conversations are held on each forum. A range of social support techniques was demonstrated, with conversations characterized by encouragement, humor, and experience-based advice.

Conclusions:

This study demonstrates that rich data on fathers’ experiences can be sourced from social media and analyzed rapidly using automated techniques, providing an additional tool for researchers exploring fatherhood.


 Citation

Please cite as:

Teague SJ, Shatte AB

Exploring the Transition to Fatherhood: Feasibility Study Using Social Media and Machine Learning

JMIR Pediatr Parent 2018;1(2):e12371

DOI: 10.2196/12371

PMID: 31518298

PMCID: 6715057

Per the author's request the PDF is not available.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.