
Using Hadoop to Measure Influence - Anon84
http://www.cloudera.com/blog/2011/05/using-hadoop-to-measure-influence/
======
alain94040
Interesting discussion (I wrote the reputation algorithm for
<http://letslunch.com>). My main concern with computing online reputation is
that you miss the 95% of the people who don't see Twitter as a goal. Is a
Senior Vice-President at Apple influential? Klout would say no (no tweets).
LetsLunch would say yes :-)

~~~
bravura
What data does LetsLunch use that allows it to score 95% of people?

On Twitter, if you are the Senior VP at Apple and---hypothetically---you only
have 50 followers but they are all movers and shakers, then Twitter analysis
should be able to determine that you are influential.

I guess your concern is that there might be many influential people who aren't
even on Twitter, or don't have 50 influential followers on Twitter. What is
your proposed solution to the problem? Your "How It Works" page
(<http://letslunch.com/site/page?view=how-it-works>) says that you pull signal
from LinkedIn and, optionally, Twitter and Hacker News. You arrange lunch
dates, collect post-lunch feedback, and then tune people's reputation based
upon the feedback.

What about the 99.99% of people who don't use LetsLunch? And why is a single
lunch date enough to be able to determine someone's influence?

~~~
alain94040
Yes, my concern is that a lot of influential people just aren't on Twitter. I
would almost argue that the _really_ influential people have better things to
do than tweet. And I agree they are not on LetsLunch either, that wasn't my
point :-)

I gave a fairly specific example. I think it's pretty self-explanatory.

~~~
bravura
Are you talking about Scott Forstall?

Despite having 0 tweets, he has 40K twitter followers:
<http://twitter.com/#!/forstall/followers>

It should be possible to determine from that information that he has
influence.

