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18 May 2004 |
Social Business Network platform Ecademy has positioned their feature to find and meet 'people similar to you' as I recently discovered. As I wrote in the blog on the 28th of April (here) Ecademy uses keywords in the profiles to describe who you are and what you want. Then, the 'find people like me' button can search other profiles and return those who have things in common. The more keywords in common, the higher the score.
It itself not an uncommon social software feature, and to my surprise they have added an automated banner on the homepage which selects (presumably at random) someone from the results list that 'has a profile like me'. The idea is good, yet I have questions about the value of this feature for me. Take this example.
Just now I was recommended Tom Smith because he has things in common with me. When I started to look at his profile, I found that there were just two keywords (of 50) that he shared with me (incidentally, "social software" and "virtual communities"). The other 48 did not resonate very much with me. Going back to the homepage and refreshing a couple of times, other names popped up and I checked their profiles likewise. Very little in common - it seems that
Ecademy is trying to use the power of volume in their attempt to create networks of people rather than quality (or perceived quality I should say). Tom Smith was not even on the list of people that 'look like me' when I forced to show a list - meaning he has less than 17% in common (...) which appears to be very much true.
The quality of this selection process can be perceived as quite shaky because Ecademy does not know which keywords are more important to me than others. I would contact Tom for his 'virtual communities' keyword but not if we shared 'tapas' in common. It's just that these keywords represent who I am and what I want, yet the engine does not discriminate between the two. Splitting the list would be much better. Ryze started off with that quite well (I have...) and (I want..) but did not implement an engine to link people with that. Perhaps it can come still, Social Business Network platforms are on the move and they go very fast.. they just have to stay away from the volume..
This happened at 2:45:56 PM or
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An interesting article in Februarys HBR contained trends to watch out for in 2004. One in particular is of interest to Ecademists:
17. Watching the Patterns Emerge
We’ve known for decades that informal social networks drive business—from employees at the watercooler to job seekers canvassing acquaintances to communities of practice. But it is much harder to map a network than to draw an org chart, and unlike org charts, social networks are self-altering. Knowing that networks are valuable doesn’t help tell us how they are valuable or how to use them.
That is changing. Three big forces are at work: our understanding of the mechanics of social networks, within and between businesses; the growing cloud of data that surrounds our every transaction; and the speed at which we’re able to react to those data.
Better Models of Social Networks. Stanley Milgram gave us the phrase “six degrees of separation” in a 1967 paper, but we didn’t understand how the six-degrees phenomenon worked for another 30 years, until Duncan Watts and Steve Strogatz finally worked out the details, described in Watts’s 2003 book, Six Degrees. This work, along with that of their peers, such as Albert-László Barabási of Notre Dame and Bernardo Huberman of HP, amounts to a revolution in our understanding of how social networks operate.
Better Real-World Data. Our lives are increasingly mediated by the Internet, from booking flights to making dates, and Web activities generate a cloud of metadata, the data that describe objects or transactions. One of the surprises with metadata is how little we need before we can start divining useful information. Amazon’s book recommendations, Blogdex.net’s lists of conversational trends on Web logs, Huberman’s maps of social networks derived from e-mail traffic—all these things and many more come from the mining of simple metadata.
Faster Reflexes. We can now work with the data in real time. Until recently, all mapping of social networks was like photography. You’d take a snapshot of a group’s relationships, develop it, and weeks or months later, you’d see how it came out. With better tools for mining social metadata, we can start to treat our social networks like mirrors, getting the information we need as we need it. Social networking sites like LinkedIn and Friendster let individuals figure out who is in their friend-of-a-friend networks, while software applications like Spoke and Visible Path map companies’ social networks to help businesses figure out whom to tap when trying to pitch a product or close a sale.
In what Kevin Werbach has called the era of “postmodern knowledge management,” it’s becoming clear that viewing a company’s knowledge as something separate from its employees is impossible. Our growing understanding of social networks may help us leverage real people’s interactions, for everything from trend spotting by scouring public conversations to identifying internal experts within a department to ensuring that a merger actually results in cooperation among employees, not just a change in logo.
Social networks can’t simply be strip-mined of their value, however. A social network is a living thing that is altered by use. There are reports that the value of networking for job possibilities is weakening, in part because so many employment experts have recommended this very strategy. Likewise, privacy concerns and employees’ inclination to see their social networks as personal assets will lead to tension between management and rank-and-file workers about both the observation and use of social networks.
Many of the social networking tools being proposed today will fail, because the obvious ideas are technologically simple but socially unworkable. (“If we all dump our address books into one big database, everybody will know everybody!”) As we get smarter about building social networking tools, however, we will take it for granted that our social networks have measurable value, as do other intangibles such as brand, and we will find ways to recognize it. Managers manage what they can see, and as they begin to see social networks, the long-term effect on the business landscape will be profound.
"Creativity is about divergent thinking. Innovation is about convergent thinking." - Ikujiro Nonaka
[from John MacAskill's blog on Ecademy]
This happened at 2:12:26 PM or
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©
Copyright 2005 Erik van Bekkum.
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