Cited by 64Health Literacy and Information AccessibilityMental Health via WritingExpert finding and Q&A systems

Describing the distribution of engagement in an Internet support group by post frequency: A comparison of the 90–9-1 Principle and Zipf’s Law

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Carron-Arthur, Bradley, Cunningham, John A., Griffiths, Kathleen M.·2014·Internet Interventions

Abstract

Sustainable online peer-to-peer support groups require engaged members. A metric commonly used to identify these members is the number of posts they have made. The 90-9-1 principle has been proposed as a ‘rule of thumb’ for classifying members using this metric with a recent study demonstrating the applicability of the principal to digital health social networks. Using data from a depression Internet support group, the current study sought to replicate this finding and to investigate in more detail the model of best fit for classifying participant contributions. Our findings replicate previous results and also find the fit of a power curve (Zipf distribution) to account for 98.6% of the variance. The Zipf distribution provides a more nuanced image of the data and may have practical application in assessing the ‘coherence’ of the sample.

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Crossref · 10.1016/j.invent.2014.09.003

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Authors
Carron-Arthur, B., Cunningham, J. A., & Griffiths, K. M.
Affiliations
Australian National University (AU)
Venue
Internet Interventions
Publisher
Elsevier BV
Published
2014-10
Volume
1
Issue
4
Pages
165-168
ISSN
2214-7829 (ISSN-L)
OpenAlex
W2025160127
Cited by
64
References
16
Citations by year
2026: 3 · 2025: 3 · 2024: 8 · 2023: 9 · 2022: 5 · 2021: 6 · 2020: 4 · 2019: 5 · 2018: 5 · 2017: 3 · 2016: 10 · 2015: 3
FWCI
9.67
Type
journal article
Language
en
Open access
Locations
  • Internet Interventions (publishedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ANU Open Research (Australian National University) (submittedVersion)
Funders
NHMRC (1059620)
Topics
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
  • Social Sciences › Psychology › Social Psychology › Mental Health via Writing
  • Physical Sciences › Computer Science › Information Systems › Expert finding and Q&A systems
Keywords
Zipf's law, online peer support groups, user engagement, post frequency, power-law distribution, depression, replication

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