I decided to fool around a bit to see if I could get any meaningful analysis out of analyzing a twitter hashtag for the conference we just attended at Mayo. Sadly after spending a decent amount of time it was a bit of a flop. It is kind of absurd that there is no easy to use website where you can check out trends and stats from twitter hashtags (will someone please develop this?). Chris did a great job that was time intensive from another health conference earlier this year. Definitely check out his presentation and what he found – great stuff: Health 2.0 Tweet Stream Analysis.

I went and grabbed what I think is 90%+ of the tweets from txfm09 and put them into a spreadsheet (after using notepad). There were over 1350 tweets as of this Friday (3 days post conference). For anyone who has more time and programming skills than I do, I have uploaded this dataset for anyone to grab at IBMs Many Eyes (thanks again to Chris for this tip). You can check the hashtag #txfm09 or if you want to see more cohesive thoughts by person, there is no shortage. The below is one visualization of 2 phrases (as opposed to 1 word) that is highly flawed (email me if you want details or ping me on twitter – @ghideas). Let me say this again – this graphic is highly flawed, but you can gather some very general overarching trends (it looks like there was lots of linking bcs of the prominence of bit ly and you can see the popularity of other terms and folks who were most prolific). Did I say this was flawed? For some reason the quality o of the picture below is poor, I have a slightly better and larger one, ping me if you want me to send it to you. Enjoy: