TY - JOUR AU - van Mierlo, Trevor PY - 2014 DA - 2014/02/04 TI - The 1% Rule in Four Digital Health Social Networks: An Observational Study JO - J Med Internet Res SP - e33 VL - 16 IS - 2 KW - social networks KW - Superusers KW - eHealth KW - 1% rule KW - Pareto Principal KW - 90-9-1 principle KW - moderated support AB - Background: In recent years, cyberculture has informally reported a phenomenon named the 1% rule, or 90-9-1 principle, which seeks to explain participatory patterns and network effects within Internet communities. The rule states that 90% of actors observe and do not participate, 9% contribute sparingly, and 1% of actors create the vast majority of new content. This 90%, 9%, and 1% are also known as Lurkers, Contributors, and Superusers, respectively. To date, very little empirical research has been conducted to verify the 1% rule. Objective: The 1% rule is widely accepted in digital marketing. Our goal was to determine if the 1% rule applies to moderated Digital Health Social Networks (DHSNs) designed to facilitate behavior change. Methods: To help gain insight into participatory patterns, descriptive data were extracted from four long-standing DHSNs: the AlcoholHelpCenter, DepressionCenter, PanicCenter, and StopSmokingCenter sites. Results: During the study period, 63,990 actors created 578,349 posts. Less than 25% of actors made one or more posts. The applicability of the 1% rule was confirmed as Lurkers, Contributors, and Superusers accounted for a weighted average of 1.3% (n=4668), 24.0% (n=88,732), and 74.7% (n=276,034) of content. Conclusions: The 1% rule was consistent across the four DHSNs. As social network sustainability requires fresh content and timely interactions, these results are important for organizations actively promoting and managing Internet communities. Superusers generate the vast majority of traffic and create value, so their recruitment and retention is imperative for long-term success. Although Lurkers may benefit from observing interactions between Superusers and Contributors, they generate limited or no network value. The results of this study indicate that DHSNs may be optimized to produce network effects, positive externalities, and bandwagon effects. Further research in the development and expansion of DHSNs is required. SN - 14388871 UR - http://www.jmir.org/2014/2/e33/ UR - https://doi.org/10.2196/jmir.2966 UR - http://www.ncbi.nlm.nih.gov/pubmed/24496109 DO - 10.2196/jmir.2966 ID - info:doi/10.2196/jmir.2966 ER -