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
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...
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doaj-e63ce2959edc40369783344c9897f7642020-11-25T02:29:54ZengElsevierInternet Interventions2214-78292014-10-011416516810.1016/j.invent.2014.09.003Describing the distribution of engagement in an Internet support group by post frequency: A comparison of the 90-9-1 Principle and Zipf's LawBradley Carron-Arthur0John A. Cunningham1Kathleen M. Griffiths2National Institute for Mental Health Research, Australian National University, 63 Eggleston Road, Acton, Canberra, ACT 0200, AustraliaNational Institute for Mental Health Research, Australian National University, 63 Eggleston Road, Acton, Canberra, ACT 0200, AustraliaNational Institute for Mental Health Research, Australian National University, 63 Eggleston Road, Acton, Canberra, ACT 0200, AustraliaSustainable 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.http://www.sciencedirect.com/science/article/pii/S221478291400027XeHealthInternet support groupSocial networkZipf's Law90-9-1 principle1% rule |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bradley Carron-Arthur John A. Cunningham Kathleen M. Griffiths |
spellingShingle |
Bradley Carron-Arthur John A. Cunningham Kathleen M. Griffiths 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 Internet Interventions eHealth Internet support group Social network Zipf's Law 90-9-1 principle 1% rule |
author_facet |
Bradley Carron-Arthur John A. Cunningham Kathleen M. Griffiths |
author_sort |
Bradley Carron-Arthur |
title |
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 |
title_short |
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 |
title_full |
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 |
title_fullStr |
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 |
title_full_unstemmed |
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 |
title_sort |
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 |
publisher |
Elsevier |
series |
Internet Interventions |
issn |
2214-7829 |
publishDate |
2014-10-01 |
description |
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. |
topic |
eHealth Internet support group Social network Zipf's Law 90-9-1 principle 1% rule |
url |
http://www.sciencedirect.com/science/article/pii/S221478291400027X |
work_keys_str_mv |
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