Just got hold of this recent study from HP Labs which demonstrates the feedback loop between attention and contributions to online communities. The abstract provides a nice introduction:
A significant percentage of online content is now published and consumed via the mechanism of crowdsourcing. While any user can contribute to these forums, a disproportionately large percentage of the content is submitted by very active and devoted users, whose con- tinuing participation is key to the sites’ success. As we show, people’s propensity to keep participating increases the more they contribute, suggesting motivating factors which increase over time.
This paper demonstrates that submitters who stop receiving attention tend to stop contributing, while prolific contributors attract an ever increasing number of followers and their attention in a feedback loop. We demonstrate that this mechanism leads to the observed power law in the number of contributions per user and support our assertions by an analysis of hundreds of millions of contributions to top content sharing websites Digg.com and Youtube.com.
What’s important about this is helping frame community management strategies to ensure the valuable ‘advocates’ in a community remain active, by ensuring the value of peer attention is factored into sustaining their involvement. This the author’s recognise if paramount as “a disproportionate number of contribution to online peer production efforts are made by a small number of very active users”. And here’s the maths that supports this:
So what sustains this feedback loop? The authors suggest that to answer this question “one needs to look into the constituents of a contributor’s potential audience”, or to put it simply the number of fans/subscribers they have — a feature of both Digg and YouTube — could well be the missing evolutionary link:
Because a considerable portion of attention a contributor receives can be attributed to her fans, the contributor’s publicity (measured by the number of fans) could act as the important missing link between popularity and productivity. A contributor with many past contributions (high productivity) naturally has many fans (high publicity). Her fans naturally pay a lot of attention to her next contribution (high popularity). This in turn incentivizes the contributor to make more contributions.
Conclusion? (1) Have a strategy to support your top contributors. (2) As part of this measurable strategy make sure the means for them to gain attention work well.
Getting these right could make the difference between success and failure in the long term. After all don’t 90% of posts get created by 1% of users, according to Jakob Nielsen?
Indeed, Nielsen adds a useful caveat to this question to highlight quantity vs quality regarding contributions:
If you display all contributions equally, then people who post only when they have something important to say will be drowned out by the torrent of material from the hyperactive 1%. Instead, give extra prominence to good contributions and to contributions from people who’ve proven their value.
Feedback loops of attention in peer production, Fang Wu, Dennis M. Wilkinson and Bernardo A. Huberman , 2009/05/12, arXiv:0905.1740 (pdf). Thanks to the Complexity Digest for the initial research reference.
Update May 2010: A simple way to boost influencers’ (not precisely the same as ‘top contributors’ but still relevant) credibility with your users is by making their content more searchable, & by promoting it via tweets & bookmarking: http://ow.ly/1FUtM
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Thanks for all the tweets! Hmm, talking about this today I wonder if the ‘Long Tail’ model might apply to the distribution of contributors in a community as it’s about a raking of popularity? See the wikipedia entry at http://en.wikipedia.org/wiki/The_Long_Tail
Just a thought at the end of Thursday.
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