You web workers are the passionate sort – we can tell by the number of comments we get here (and we love you for it!). But for most people, leaving well thought out, useful comments on blog entries is an act of pure charity: your effort in doing so is largely lost when things scroll off the front page. Wouldn’t it be nice if the people who took the time to reflect and help others in comments could build up their social capital and be recognized?
That’s the premise behind SezWho, a relatively new service that is trying to turn blog comments into a cross-site social network. The idea is pretty simple: blog owners install a plug-in (WordPress or Movable Type at the moment, though they plan to support other platforms in the future), which adds AJAX functionality and a connection to the SezWho service to their blog comments. At that point, readers can rate any comment by clicking buttons. SezWho keeps track of ratings on a commenter-by-commenter basis, not just on a single blog, but across all blogs in their system. At any point you can see the reputation of anyone in the system, as well as all of the comments they’ve made and the ratings that they’ve garnered.
Will it work? Well…maybe. There are two big hurdles to this sort of system succeeding. The first is that it faces the usual chicken-and-egg issue of needing to spread widely to be useful, and needing to be useful to spread widely. Right now you can see SezWho in action on a few sites like Read/Write Web and VentureBeat; it seems like SezWho ought to be promoting the heck out of a directory of enabled sites to try to build an ecosystem here, but they aren’t doing so yet. The second issue is that, as sites like SlashDot and Digg have shown, reputation systems inevitably get gamed as they gain in popularity. SezWho says they’re using “a proprietary page-rank-like recursive algorithm based on reputation score of rater and commenter, their frequency of participation, time of interaction, consistency of participation and topic of discussion” to rate people. As they grow, the challenge will be to keep this algorithm tuned so that its results match our gut feeling of who is providing useful feedback. If they can do that, this could ultimately be a service that grows some legs.