One of the interesting things about this new game is that it supports user-contributed content: anyone can use the built-in level creator to create new levels and upload them to a central content server.  You can also download and play levels that others have created.  As expected, I found a few really fun levels and a bunch of not-so-good levels.  Fortunately, the Boom Blox online system allows users to rate levels with 1-5 stars, and you can sort the levels by rating when looking for new levels.

This is a great example of how this user-contributed content is becoming pervasive.  Even games like Boom Blox have a user-contributed content portion of the game.  And I think that this feature could have benefited from hiring someone who studies incentive-centered design.  There is a basic contribution question here: why should users contribute levels?  And more importantly, what types of levels should users contribute?  So far, the creators of the game have been rewarding complex Rube Goldberg type levels by highlighting them on YouTube.  It would be interesting to think about different ways that the game can reward other types of levels; for example, it could pick the highest rated levels of each type currently in the game and make them available as a downloadable “level pack.”  This might encourage users to create interesting new levels to extend the game’s current gameplay.

Another ICD issue is the rating system.  Right now, after playing an online level, the user is asked to rate it with 1-5 stars.   But, why should the user provide a rating?   And, more importantly, what metric should he or she employ?  A level might get 5 stars on “cool” but 1 on “playability”.  By thinking about what behavior you want people to do, you can design the system to elicit that behavior.  For example, you might want people to rate levels based on how much fun they are to play over and over. Do elicit that type of rating, the designers might allow people to save levels from online (which is currently supported) and automatically sort them by the rating I gave it by default.   Levels I give 5 stars are shown first, then 4 stars and on down.  This way, levels I have an incentive to rate highly the levels I want to play again (to make them easy to find), and rate poorly the levels I don’t.

This is actually an example of the side effect mechanism I’ve talked about before.  Users have a private reason to rate levels — to make it easier to find the ones they want to play again.   And the incentive to rate levels is aligned with the goals of the consumers, who want to use the ratings to know what levels are best to play.

However, making this work isn’t quite as easy as it sounds.  You need to make sure that the information users contribute is actually useful for other people. Take del.icio.us, again, as an example.  Users contribute “tags” or keywords by associating them with specific bookmarks.  I bookmark the NYTimes website, and then I can associate tags like “news” and “newspaper” and “reporting” with it.  But these words aren’t really that useful to other people.  If I search on “newspaper”, I get almost 150,000 hits, and the whole first page is news stories about newspapers and not newspapers themselves.   The tag “news” is even worse, it has over 2.5 million hits, most of which are links to actual news stories. These tags are a really bad way to find news sites.

The reason these tags don’t work can be explained by looking at how these tags are contributed in the first place.  Users choose tags to help themselves organize their own bookmarks.   When I am bookmarking a website, I try to come up with words that help me organize my bookmarks; but I don’t care about anyone else’s bookmarks or tags.  This means that when I chose to use the word “newspaper” for the NYTimes, I didn’t care if I was using it in the same way as other people, or if my using it added clutter for other people who are using that tag.  I just wanted to be able to re-find my favoriate newspaper in the future.  In short, I have no reason to choose tags in a way that helps other people.

Bookmarks, on the other hand, are different.  When I choose to create a bookmark on del.icio.us, I do think about clutter problems.   I try not to bookmark too many websites because each new bookmark makes it harder for me to my old ones.   If I bookmark too much, things get cluttered and I can’t find anything.   Tags help, but only if I use them consistently and sparingly.  But this means that if you share an interest with me, you can go to my bookmarks and they will be useful to you.  Right now, most of my bookmarks recently have been about social computing research, so if you are interested in that, head over to my bookmarks and you’ll find a relatively clutter-free set of links.

Bookmarks on del.icio.us are an example of incentive alignment.  Del.icio.us induces me to contribute information (bookmarks) in a way that the resulting contributes are actually useful to others.  Looking at any single person’s bookmarks is usually a good way of finding links to websites on topics related to that person’s interest. Each user tries to limit the clutter in his or her own bookmarks, and that helps other users make use of those bookmarks. Tags on del.icio.us represent an incentive mis-alignment.  The structure of del.icio.us gets me to contribute tags, but the tags that I contribute are almost useless to other users because I don’t take into account the additional clutter my use causes for other users.

When designing a social computing system, giving users a private, individual reason to contribute can be a powerful motivator.   And making those contributions public as a side effect can provide lots of value to the other users on the system.  But, when doing this, be careful to make sure that the incentives are aligned; that users contribute information in a form that is actually useful to others.  Make sure that concerns like clutter that are important to the users of the information are considered by the contributors when making their contributions.

Rick Wash and Emilee Rader. “Public Bookmarks and Private Benefits: An Analysis of Incentives in Social Computing.” In American Society for Information Science and Technology (ASIS&T) Annual Meeting (2007).

Del.icio.us has a great way to deal with this problem.  They sidestep the whole “strategic” problem by giving people a mostly personal reason to bookmark.  Users on del.icio.us choose their bookmarks primarily because they think that they might go back and visit the website sometime in the future.   And tags are chosen mainly to support this potential re-finding activity; users tags are chosen to help themselves organize their collection of bookmarks.   Users create these bookmarks for personal reasons, and would continue to do so even if no one else ever saw them.

However, del.icio.us makes all bookmarks public by default.  Anyone can go and view my bookmarks or anyone else’s bookmarks.   This public benefit is a side effect of the private incentives that users have to create bookmarks.  The main purpose of creating bookmarks isn’t to benefit others, but this benefit happens because of the default-to-public nature of the site.

This suggests a more general mechanism for inducing user contributions.   Social computing systems can provide a strictly private benefit from contributions — potentially by emulating something that users already do on their computers like store bookmarks — and then make these contributions public by default.  Making things publicly available as a side-effect of normal, personal use is a great way encourage contribution to a social computing system.

Rick Wash and Emilee Rader. “Public Bookmarks and Private Benefits: An Analysis of Incentives in Social Computing.” In American Society for Information Science and Technology (ASIS&T) Annual Meeting (2007).