StatBot Delivers Again: FriendFeed “Likes” Compatibility Index

FriendFeed “Likes” Compatibility Index Pre-Pre-Pre Alpha – The StatBot – Fun stats. Visualizations. Leaderboards. I know that I’m probably starting to sound like a broken record with regards to FriendFeed, but I think that they are doing some of the most interesting things on the internet right now.

Yuvi Sense has yet another great StatBot report. This time he’s analyzing “likes” compatibility on FriendFeed.

He’s analyzed Louis Gray, Robert Scoble and is now analyzing individual users by request in the comments section.

In my case, my “like” compatibility ranks the following users as liking the same sort of things as I do.

  • susanbeebe – 51
  • bhc3 – 50
  • shey – 47
  • scobleizer – 41
  • louisgray – 36
  • mitchelltsai – 34
  • dobata – 32
  • atul – 32
  • mortonfox – 32
  • nikpay – 26
  • ha3rvey – 25
  • mikereynolds – 24
  • alejandroz – 23
  • solacetech – 23
  • bwana – 22
  • beardeddave – 22
  • webomatica – 22
  • anjrued – 21
  • mrsth – 20
  • eng1ne – 19
  • ontarioemperor – 18
  • trishussey – 18
  • akiva – 18
  • jbaldwinconnect – 17
  • furry – 16
  • bluecockatoo – 16
  • maryam5063 – 16
  • This is a fantastic way to find new people that you might like to subscribe and follow. There were a few people on the list above that I was not following and so I added them. It would be interesting to see FriendFeed use technology like this also to influence the “recommended” people for me to follow. If there is a high correlation between me and someone who likes things like I do, they would seem to be potentially high value people to follow.

    You can follow me on FriendFeed here.

    Nice work as always Yuvi!

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    1. Anonymous says:

      do mine: drthomasho

    2. Thomas Ho says:

      do mine: drthomasho

    3. Yuvi says:

      Thanks Thomas – Glad I could be of any use!

      P.S. What do you think of a Flickr statbot?

    4. Aaron says:

      Using compatibility/like information is the whole premise behind the aggregator service which launched in private beta yesterday. Strands has a history of building recommendation algorithms, it makes sense to apply those algorithms to a social network. When Strands goes public and builds up a decent network of folks, it can outdo FriendFeed.

      Thomas, drop me an email (ahockley at gmail) and I might be able to get you an invite code if you’re interested.

    5. Anonymous says:

      where do I find MY stats?

    6. Thomas Ho says:

      WHERE do I find MY stats?

    7. Yuvi says:

      Thomas Ho: Well, you have only 24 likes, so it’s hard to apply. Anyway, first is Tris Hussey with 7 shared likes, next is Mitchell Tsai with 6, Louis Gray with 6 and Thomas Hawk with 5….