Comments on: Better Popularity Metrics For Twitter http://w-shadow.com/blog/2009/03/20/better-popularity-metrics-for-twitter/ A blog about web development, software business, and WordPress Wed, 08 Feb 2012 21:10:53 +0000 hourly 1 http://wordpress.org/?v=3.3.1 By: White Shadow http://w-shadow.com/blog/2009/03/20/better-popularity-metrics-for-twitter/comment-page-1/#comment-158643 White Shadow Mon, 03 Jan 2011 19:22:52 +0000 http://w-shadow.com/?p=1000#comment-158643 That's a good point, and it illustrates that attention metrics can get hairy fast. For example, suppose I follow someone who lives in a different time-zone. Even if they tweet a lot, I might miss or ignore most of their tweets because I'm <em>asleep</em> when they arrive. That’s a good point, and it illustrates that attention metrics can get hairy fast. For example, suppose I follow someone who lives in a different time-zone. Even if they tweet a lot, I might miss or ignore most of their tweets because I’m asleep when they arrive.

]]> By: Giles Bowkett http://w-shadow.com/blog/2009/03/20/better-popularity-metrics-for-twitter/comment-page-1/#comment-158624 Giles Bowkett Mon, 03 Jan 2011 18:57:46 +0000 http://w-shadow.com/?p=1000#comment-158624 This is a good idea but it has a pretty gigantic hole in its logic: it assumes an even distribution of attention across all followed accounts. In fact such distribution is wildly uneven and probably conforms to a power law. If I follow two people, and one of them tweets every month while the other tweets every minute, it's pretty obvious that one of these people gets much more of my attention than the other. Obviously a contrived example but in real life people like Scoble get unfollowed because of excessive tweet frequency. Probably some amount of data mining would be necessary to quantify that dimension. You'd need a reasonable picture of per-account frequency and obviously those frequencies show varying degrees of stability (simple real-life example, one person I follow tweeted way more than usual over the holidays because they were stuck in an airport and bored). This is a good idea but it has a pretty gigantic hole in its logic: it assumes an even distribution of attention across all followed accounts. In fact such distribution is wildly uneven and probably conforms to a power law. If I follow two people, and one of them tweets every month while the other tweets every minute, it’s pretty obvious that one of these people gets much more of my attention than the other. Obviously a contrived example but in real life people like Scoble get unfollowed because of excessive tweet frequency.

Probably some amount of data mining would be necessary to quantify that dimension. You’d need a reasonable picture of per-account frequency and obviously those frequencies show varying degrees of stability (simple real-life example, one person I follow tweeted way more than usual over the holidays because they were stuck in an airport and bored).

]]> By: White Shadow http://w-shadow.com/blog/2009/03/20/better-popularity-metrics-for-twitter/comment-page-1/#comment-21706 White Shadow Fri, 20 Mar 2009 23:13:48 +0000 http://w-shadow.com/?p=1000#comment-21706 The way TweetTop works reminds me more of <a href="http://alltop.com/" rel="nofollow">AllTop</a> not WeFollow. Having the algorithm implemented in a real site would definitely be interesting. The way TweetTop works reminds me more of AllTop not WeFollow.

Having the algorithm implemented in a real site would definitely be interesting.

]]> By: Jordan Willms http://w-shadow.com/blog/2009/03/20/better-popularity-metrics-for-twitter/comment-page-1/#comment-21689 Jordan Willms Fri, 20 Mar 2009 20:41:13 +0000 http://w-shadow.com/?p=1000#comment-21689 Great article. Check out http://www.TweetTop.com for who to follow on twitter in many different categories. Similar to wefollow but a mix of UGC and editorial controlled (as opposed to wefollow which lets users self classify). I'd like to incorporate some of your thoughts into tweettop.com for a better ranking algorithm. This could, theoretically remove our need for manual editorial control. J Great article. Check out http://www.TweetTop.com for who to follow on twitter in many different categories. Similar to wefollow but a mix of UGC and editorial controlled (as opposed to wefollow which lets users self classify).

I’d like to incorporate some of your thoughts into tweettop.com for a better ranking algorithm. This could, theoretically remove our need for manual editorial control.

J

]]>