Web 2.0 is a term that signifies the revolutionary movement from the static web to the social or the participatory web. Since the early days of the web, there were publishers and there were readers but with the advent of tagging systems, blogs, wikis, RSS and user generated content, the focus of power is shifting and the traditional media as well as the publishing is seeing a sea of change. Community is one very important aspect of this web 2.0 scenario and as James Surowiecki wrote in his bestseller “The Wisdom of Crowds”, this aspect can offer a lot to individuals, businesses and anyone who is directly or indirectly connected to the web.
It is a well known fact that given you offer the right challenge and an interesting interface, the crowd will be much wiser than any single participant. This is true offline as well as online. When we see examples like the search engines results page on Google.com or the “Most Emailed” stories on Yahoo or the highest rated videos on Youtube, this is the collective wisdom in strict web 2.0 scenario. You can too harness the crowd wisdom to maximum potential if you keep the following points in mind before crafting your web 2.0 feedback systems
One Way Communication – Uncomplicated System Design
Your feedback/data systems should have a one way communication which accepts input from users. As away from Web 2.0 it may sound, the matter of fact is that conversational systems are too complex to be understood by the “Wisdom of Crowds” logic. You may have a complex project at hand but until you break it down into the simpler or rather simplest components, it would be difficult to get the best feedback.
Interaction Design
If the community or the participants have to think too much, they will be confused and even the best intentions can’t help the feedback systems from failing. Systems that offer feedback in form of thums up/down, rating on a scale of 1 to 10 or drawing on a map may work the best.
Data Aggregation
The web 2.0 feedback systems should have an aggregator which can be an algorithm or just a mathematical function that computes the feedback to come to a results. Google’s legendary PageRank algorithm is an aggregator of its sorts which computes the relevance and authority of links to come up with rankings corresponding to user queries.
Audience
As pointed in the book by Surowiecki, the wider and diversified the audience, the better. This is where web 2.0 gets complete opposite of chat rooms and forums where usually the discussion and the feedback quality falls when the participation grows. Balancing out the audience is the basis for great web 2.0 systems.
Motivated for Self
In the stock market, all the investor thinks about is his or her own bottom line and this approach works well. The website owners who link to different pages are doing for their self motive whether that is better information or related content (or money) but inadvertently they are feeding an algorithm that is producing great results based on this collective linkage data.
Results Display Too Soon Too Much
Ranked results should be avoided since they are capable of inducing biases in the feedback system since it creates a group behavior which pollutes the integrity of data. Feedback results can be posted in stages so that they do not affect the self motives of the crowds. Also possible is showing a list of mixed results or best results instead of a ranked list. The users should be disclosed the results of a polling only after casting their own vote.
These aspects of the Wisdom of Crowds are just the start for your web 2.0 savvy business— there’s a lot more to learn and to include in your day to day offerings. . Be sure to read Surowiecki’s book. And remember, this is a constant quest which should evolve over time.
Author Resource:
Asmita is a leading web 2.0 design and development speacialist and runs a company at http://www.vinfotech.com/ and a web 2.0 blog at http://bhopu.com .
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