The 90.9.1 Rule: Online Participation Inequality RatioEdit
“In most online communities, 90% of users are lurkers who never contribute, 9% of users contribute a little, and 1% of users account for almost all the action.”(1)
Definition / Concept (what is it, how did it come to be, why those ratios?)Edit
The 90-9-1 principle states that a mere 1% of the users contribute most content, 9% of users contribute a little, and 90% of users do not contribute at all. The term 90-9-1 principle was coined in 2006 by Jakob Nielsen of the Nielsen/Norman group (1), but the concept of participation inequality has been studied since the early 1990's.(2)(3)
Inequality Online (what it’s used for, which industries use it etc.) Edit
It's primarily used for marketing purposes in primarily B2C companies such as retail, CPG etc.
90.9.1 Rule Applied to Social Media (blogs, company outreach, how does it work) Edit
It should work very similar to how it might in large physical groups. In physical groups there are some very active users/posters/commenters, some people liking or briefly participating in those conversations and some lurkers. However social media has given everyone a stronger voice which doesn't take too much effort to use and the omnipresence of social media platform aids in that as well. Therefore the split would not be 90.9.1 but more like 50.40.10.
Future of the 90.9.1 Rule (will this continue to hold true?, what downfalls does it have) Edit
The rule will exist in spirit but will get more skewed towards 50.40.10 thanks to the presence of social media. Additionally, with the advent of big data and targeted marketing we should see more focused marketing approaches resulting in more specialized groups thereby increasing overall participation.
Benefits and Downfalls of the 90.9.1 Rule (pros and cons of using the rule) Edit
A pitfall of the 90-9-1 rule is that the 1% of users who are most visible may have different demographic characteristics or views than the average member of the community. This can lead to bias when the contributions in the online community are used for data analysis, and then extrapolated to the general community. An example would be online customer feedback and reviews. It is not unlikely that reviews and feedback are posted mainly by elated or very dissatisfied customers, who may not have wishes that are representative of those of the general population. Catering those customers only may lead to changes that are detrimental for the (larger) silent customer base.
An advantage of the 90-9-1 rule is for example a knowledge-sharing platform like wikipedia, even though the participation rate is even lower, it is not necessary a downside. Because promoting high quality contribution is more important than the quantity. Also, different information from a diverse group of people will confuse the readers.
It sounds negative that only 1% really contribute, but is it? Looking at "Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia" Zhang and Zu (4) show that the incentive to contribute is partly based on the size of the group of lurkers. From that perspective a shift in the 90.9.1 distribution would lead to less input instead of more.
Other Information (anything you find interesting that doesn’t fit into an above category) Edit
- Fonken, L. (2015). The 90.09.01 Principle; The 900 Human Species. 1st ed. [ebook] Available at: http://www.lulu.com/shop/luis-daniel-maldonado-fonken/the-900901-principle/ebook/product-22324820.html [Accessed 29 Feb. 2016].
References (please help us with quality content!) Edit
(1) Nielsen, J. (2016). Participation Inequality: The 90-9-1 Rule for Social Features. [online] Nngroup.com. Available at: https://www.nngroup.com/articles/participation-inequality/[Accessed 1 Mar. 2016].
(2) Hill, William C.; Hollan, James D.; Wroblewski, Dave; McCandless, Tim (1992). "Edit wear and read wear". Proceedings of the SIGCHIconference on Human factors in computing systems (ACM): 3–9.doi:10.1145/142750.142751. ISBN 0-89791-513-5.
(3) Whittaker, S., Terveen, L., Hill, W. and Cherny, L. (2003). The Dynamics of Mass Interaction. From Usenet to CoWebs, pp.79-91.
(4) Zhang, X., and Zhu, F., "Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia," American Economic Review, 101, 4, 2011, 1601-1615.