Twellow’s search ranks Singapore’s top twitter users by no. of followers
After today’s lunch at the CIT 2008 conference, Ken wanted to know how I fed my online activity (i.e. lifestream) into Twitter. He was referring to those links I have automatically published with prefixes , [del.icio.us], and so on as seen in my twitter archives.
Picking a rather nice technology lecture room, I showed him (and intrigued passer-bys) how I used twitterfeed.com, by giving it my twitter credentials, feeding it various RSS feeds (I gave three), adding prefixes, polling times and so on. I stressed that this sort of service could easily be abused, and recommended polling once an hour with 1 item per feed so as not to flood or spam the entire twitter stream.
For instance, I were to share 5 new blog posts within one hour, Twitterfeed will only tweet the latest one. Think of it as a tease for your twitter followers.
Apart from this demo, a major portion of my recent real-world conversation has been dominated with talk about twitter, which has prompted me to think of it as the a suitable topic of my next web workshop. As I’ll be addressing an academic crowd at the Teaching & Learning Center (TLC), the tentative workshop title will be “Twitter Tricks for Tenacious
Potentially useful beyond academia, I’ll be showcasing the various twitter tools you could use for 1) networking, 2) tagging, 3) surveying, 4) visualizing trends, 5) media monitoring, and much more…
As third party twitter tools improve, so will the resolution of our twitter dataveillance. For example, my early method for deriving Twitter user population by country (April 2008) can now be more granular and persistently updated.
As seen above, I just played with Twellow and found it to be a specialized twitter search based on individual profiles. You can browse twitter users based on profession, or as I’ve tried, go by country (Singapore) and possibly any keywords. Results are ranked by users with the most followers, as an indicator of personal influence or reputation (not too far from how Google Pagerank works). This is more useful than how I used twitter.com’s built-in search to find users by geography.
I’ll also be covering the shortcomings of researching within the twittersphere. Top of mind is how the recurring service downtime has a cascading effect on all related services. This is probably why most of the third party Twitter search engines are either displaying older results (e.g. your followers count on Twellow is out of date), or missing entire parts of your twitter stream (e.g. summize doesn’t have 100% of your archives).
That’s a taste of things to come.
As always, I tend to share notes, slides and videos of the presentations I give. If you know of anything I should cover for this upcoming twitter workshop, do drop me a line!