our work on community analytics, and what it tells us about Wikipedia's problems and possible solutions. Naoko Komura (pictured at right) of the Wikimedia Usability Initiative, as well as Eric Zachte, the staff data analyst (also pictured at right), spoke very eloquently about how we can create social tools to direct the best social attentions to the needed parts of Wikipedia.
Fundamentally, Wikipedia has always had a "people-ware" problem: the distribution of the expertise that is freely donated to the right places. It has been and always will remain its greatest challenge. The amazing thing about Wikipedia is that it managed to do this for so long, such that a valuable knowledge repository can be built up as a result. At first, people simply came because it was the place to be. Now, we have to work a little harder.
We spent a lot of time talking about the best way to model this people-ware problem, either using biological metaphors (evolutionary systems with various forces), or economic models (see last post here). However, one thing to be aware of is the danger of "analysis paralysis", where you spend so much time analyzing the problem, and forget that there are already many ideas that have been generated for moving the great experiment forward.
For example, there are many places in Wikipedia that are not well populated. It's well-known that many scientific and math concept articles, for example, could use an expert-eye to catch the errors and explain the concepts better. How can we build an expertise finder that would actually invite people to fix problems that we know exists in Wikipedia?
Chris Grams blogs about a part of this idea here. We suggested some time ago to have a system like WikiDashboard, where you actually show the readers what the social dynamics have been for a particular article.
Wikipedia was created in 2001, when social web was still in its infancy. During the ensuing 9 years, it has changed very little, and I would argue Wikipedia have not kept up with the times. Lots of "Social Web" systems and new cultural norms have been built up already. For example, I suspect that many of us would not mind at all to reveal our identities on Wikipedia, and we might like to login with our OpenIDs and even have verified email addresses so that the system can send me verification/clarification/notification messages. The system perhaps should connect with Facebook, so that my activities (editing an article on "Windburn") is automatically sent to my stream there. My friends, upon seeing that I have been editing that article, might even join in.
I think that Wikipedia is about to change, and it is going to become a much more socially-aware place. I certainly hope that they will tackle the People-Ware (instead of the Tool-Ware) problems, and we will see it become an exciting place again.
Monday, March 8, 2010
Thursday, March 4, 2010
Many people have already stolen the attention-scarcity ideas from Herb Simon and said that the most important problem in our information overloaded society is the efficient distribution of attention. What some have called the "attention economy" is nothing more than a re-packaging of this idea.
In business, of course, getting the consumers' attention is quickly becoming an important aspect of being successful. Traditional ways of getting people's attention is through advertisement, and we have witnessed a dramatic transformation of how advertisements work in the online world in the last decade, from display advertising to search advertising and, more recently, further to action advertising. Increasingly, we can tie advertising dollars to direct consumer action.
For us, it was not a stretch, then, to start thinking about how the consumer actions are starting to quickly feedback to product design. Thus, we now have people talking about crowdsourced product designs. The most agile companies now listen to the consumers via channels such as Facebook, Twitter, and Blog analytics. They do this via services such as brand management consultants and sentiment analysis tools, so much so, they are able to discern tiny changes in consumer awareness of product issues and their desires.
We know also that traditional economic models serves to optimize the distribution of products to people who want them. But these models have also recently been used to optimize the distribution of people's attention to products that might serve their needs. The two usages obviously goes hand-in-hand.
If we can help companies to serve people attention spots just-in-time with the best products, we would have a highly optimized economy that wastes little energy in distributing worthless advertisements (or spam). In fact, the existence of spam points to the inefficiencies in the economic system.
Turns out that versions of this problem exists everywhere in the Web2.0 world:
- The problem of efficiently distributing the best tweets to the people who want to view them is a version of this attention distribution problem. Any time you see a tweet that was worthless to you is an opportunity for optimization.
- The problem of pointing experts to the most valuable articles that they can contribute to in Wikipedia is another version.
- What if we can design an expertise finding system that recommends the best articles for you to contribute to in Wikipedia? Would it increase participation rates?
- What if we analyze your social network everyday and tell you the best tweets that you should spend five minutes on? Would more people retweet more often?
- What if product designers are better tuned to trending topics and needs, would they enable companies to succeed more often? Are companies like Zazzle and Cafepress the prototype examples of lubricating this path?