This paper is in the following e-collection/theme issue:

Social Media for Parenting (42) Machine Learning (1663)

Published on in Vol 1, No 2 (2018): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12371, first published .
Exploring the Transition to Fatherhood: Feasibility Study Using Social Media and Machine Learning

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

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

Authors of this article:

Samantha J Teague1 Author Orcid Image ;   Adrian BR Shatte1, 2 Author Orcid Image
Article Authors Cited by (15) Tweetations (15) Metrics

Journals

  1. Shatte A, Hutchinson D, Fuller-Tyszkiewicz M, Teague S. Social Media Markers to Identify Fathers at Risk of Postpartum Depression: A Machine Learning Approach. Cyberpsychology, Behavior, and Social Networking 2020;23(9):611 View
  2. Robila M, Robila S. Applications of Artificial Intelligence Methodologies to Behavioral and Social Sciences. Journal of Child and Family Studies 2020;29(10):2954 View
  3. Shatte A, Hutchinson D, Teague S. Machine learning in mental health: a scoping review of methods and applications. Psychological Medicine 2019;49(09):1426 View
  4. Sutter C, Pham G, Yun J, Narang K, Sundaram H, Fiese B. Food parenting topics in social media posts: Development of a coding system, examination of frequency of food parenting concepts, and comparison across Reddit and Facebook. Appetite 2021;161:105137 View
  5. Livingston J, Youssef G, Francis L, Greenwood C, Olsson C, Macdonald J. Hidden in Plain Sight? Men's Coping Patterns and Psychological Distress Before and During the COVID-19 Pandemic. Frontiers in Psychiatry 2022;12 View
  6. Westrupp E, Greenwood C, Fuller-Tyszkiewicz M, Berkowitz T, Hagg L, Youssef G, Mahmoud A. Text mining of Reddit posts: Using latent Dirichlet allocation to identify common parenting issues. PLOS ONE 2022;17(2):e0262529 View
  7. Smith I, Youssef G, Shatte A, Teague S, Knight T, Macdonald J. “You are not alone”: A big data and qualitative analysis of men's unintended fatherhood. SSM - Qualitative Research in Health 2022;2:100085 View
  8. Yilmaz M, Korukcu O, Kabukcuoglu K. The Effect of Skin-to-Skin Contact Between Father and Baby on Paternal Attachment. Current Psychiatry Research and Reviews 2022;18(3):248 View
  9. Cameron E, Simpson K, Pierce S, Penner K, Beyak A, Gomez I, Bowes J, Reynolds K, Tomfohr-Madsen L, Roos L. Paternal Perinatal Experiences during the COVID-19 Pandemic: A Framework Analysis of the Reddit Forum Predaddit. International Journal of Environmental Research and Public Health 2023;20(5):4408 View
  10. Thornton C, Lanyi K, Wilkins G, Potter R, Hunter E, Kolehmainen N, Pearson F. Scoping the Priorities and Concerns of Parents: Infodemiology Study of Posts on Mumsnet and Reddit. Journal of Medical Internet Research 2023;25:e47849 View
  11. ÇİTİL AKYOL C, SUMBAS E. Sosyal Medyada Ebeveyn Olmak: Babalar Nerede?. Abant Sosyal Bilimler Dergisi 2023;23(3):1282 View
  12. ŞEKER S, ÇİTİL CANBAY F. Identifying Web-Based Training and Pregnancy School Experiences of Father Candidates: A Phenomenological Study. Fenerbahçe Üniversitesi Sağlık Bilimleri Dergisi 2023;3(3):435 View
  13. Cameron E, Simpson K, Bowes J, Pierce S, Penner K, Beyak A, Gomez I, Reynolds K, Roos L. A Qualitative Forum Analysis of Fathers’ Stressors and Support Seeking Behaviour During the COVID-19 Pandemic. Journal of Family Issues 2024 View
  14. Feuerriegel S, Maarouf A, Bär D, Geissler D, Schweisthal J, Pröllochs N, Robertson C, Rathje S, Hartmann J, Mohammad S, Netzer O, Siegel A, Plank B, Van Bavel J. Using natural language processing to analyse text data in behavioural science. Nature Reviews Psychology 2025;4(2):96 View
  15. Eldeeb N, Ren C, Shapiro V. Parent information seeking and sharing: Using unsupervised machine learning to identify common parenting issues. Children and Youth Services Review 2025;172:108210 View