The KOL Miner's Daughter

by Deborah Volk on May 11th, 2009

Just when you've escaped from your past, it comes back to haunt you, something about learning from history and being doomed to repeat it. I had every intention of doing a blog post about identity management challenges associated with implementing business processes having to do with internal (employee) transfers but when worlds collide, singularity happens. Prodded by the announcement of an improved Twitter search, Oracle's Nishant Kaushik writes about the new "identity equation" This comes only two days after a blog on the very same subject by a former colleague of mine, Endeca's chief scientist Daniel Tunkelang. Two blogs, two completely different perspectives. It seems the world is all atwitter (pun intended) about the wealth of information Twitter has to offer (MONEYtization, anyone?)

These two blogs reminded me of a problem I worked on briefly soon after I started Identigral. Given a large body of information that may include everything from blogs, news articles, conversations on Twitter (then yet to be born), to published and peer-reviewed research, how do you identify people whose opinions carry weight. This problem is especially potent in the pharma industry because physicians who are (more) respected by their peers can help product sales by mere advocacy, not to mention a more concerted effort. Both bottom-line (marketing dollars) and top-line (revenue) is impacted and there's a small cottage industry oriented toward solving this problem in pharma. This challenge even has a name, it is known as Key Opinion Leaders (KOLs).
KOLs is not something new, it's been around for a long time but methods and techniques have evolved along with decreasing cost of computational power, thus making it easier to construct a decent solution at a fraction of the cost. Twitter makes this more interesting, because now instead of having a bunch of doctors talking about clinical trials, you have doctors, engineers, teachers, kids, all 140-charactering about their aspects of the same problem (did this miracle cure work?), muddying the water and making data mining algorithms sweat. (They secrete residuals).
Nishant is correct in stating that reputation will need to have a context, just like Key Opinion Leaders have their sphere of influence. Just because you can teach a class on theoretical physics doesn't mean you know how to fix my car. On the other hand, even if reputation is context-based, it doesn't necessarily mean the search result will be relevant. If I am an Oracle Identity Manager (OIM) expert, when I search for "OIM" on Twitter, should I see OneInchMan's (who uses the Twitter tag #oim) thoughts about psychedelic music or should I see Nishant's announcements of recent Oracle whitepapers? Perhaps Twitter should prioritize the search results for me by putting Nishant before OneInchMan. Two KOL's, two different worlds but the "right" answer would be based on the context of my search in relationship to the KOL's sphere of influence, including historical data (past tweets) as fodder for algorithmic scoring of intersection between the two.

We now return back to our regular programming...

Posted in not categorized    Tagged with twitter, contextual search


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