The most basic problem that any social media system faces is contribution; the system needs contributions from its users. These contributions are usually in the form of some type of information: text, images, videos, etc. The fact that these contributions come from end users is what makes these systems social media. For most systems, users will not naturally volunteer to spend their time and effort contributing, so good social media systems include some mechanism that induces at least some of its users to contribute information. One nice thing about these technological systems is that identifying users is fairly easy, and it is possible to prevent or exclude users from accessing the contributions of others.
Threatening to exclude users can serve as a strong motivation for users to contribute information. The simplest way to do this is with a minimum threshold: any user who does not contribute the minimum amount of information to the system will be excluded from accessing the system. Technically, this is a very simple mechanism to implement; however, it is not clear how users will react to such a threat.
Jeff MacKie-Mason and I constructed a mathematical model of behavior to try to predict what will happen when a system uses a minimum threshold to try to induce greater contributions. It turns out that the behavior is not straightforward; some users will increase their contributions to the minimum in order to continue receiving access. Other users will decide that its not worth it anymore and stop using the system. It is actually the users with the lowest marginal net benefit that will stop using the system. These are the users who get the least benefit out of the first piece of information they contribute. Users with more moderate marginal net benefits are the ones that will increase their contributions to meet the threshold.
Overall, what the minimum threshold does is produce greater equality of contributions. Without the threshold, there is a wide variance in how much information each person contributes. The threshold pushes everyone to contribute a similar amount as everyone else, reducing the variance in contributions.
We also use this model to provide concrete design advice. When does it make sense to use a mechanism like this? This mechanism works best when there are a lot of users in the system. This is because the minimum threshold acts kind of like a coordinating device; many users all coordinate and contribute that minimum. More users in the system create a larger multiplier on the minimum threshold, leading to a much larger amount of information for everyone. It also works best when, without the threshold, very little information is voluntarily contributed. A system where lots of information is already contributed doesn’t need more users contributing, and runs the risk of unnecessarily hurting people by forcing them to contribute more information than they would prefer to.
Rick Wash and Jeffrey MacKie-Mason. “Using a Minimum Threshold to Motivate Contributions to Social Computing” 2009
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