Sunday, December 19, 2010

Twitter omphaloskepsis

Twitter is an inherently narcissistic medium. There are many valid information-sharing and collaborative uses, but overall I typically interpret a person's twitter stream as a crude reflection of their raw interests and personality. "This is what's on my mind, right now."  

Topic frequency within my Twitter stream

I decided to export my extant Twitter stream and perform some superficial analysis to see what I like to drone about. I passed the 1,000 tweet mark, and I felt that this was a sufficiently large body of text so as to be representative. While I don't have very many followers, I'd nevertheless like to thank all of them for their peculiar interest in what I have to say -- however banal or anodyne.

Blah blah blah
Clearly I enjoy nattering on about my work, and about software and technology. Life at a nascent software startup occupies the attention like few other things. It's not exactly scintillating subject material--but that is what is important to me, apparently. Narrowly squeaking into third place are tweets about the dynamic city I reside in, Toronto. I self identify as a climber, skateboarder, and runner, so it's not surprising to see those topics up there as well.

A simple conclusion to draw from the chart is, if the listed topics don't appeal to you, you're probably not going to want to follow me!

Methodology
I exported my Twitter stream with a free online tool called Tweetake [now defunct, alas. Twitter subsequently released directions on how to export your twitter archive], winding up with a tidy .CSV file. Then I manually went through each entry in Excel and tagged it with a keyword (or multiple keywords) depending on the subject matter. The last step was to generate a simple graph based on the keyword frequency.

Other areas for exploration
There are numerous areas for further analysis--except really, who has the time for that sort of foolishness? If I had a virtual assistant I would set them off on a report of:
  • time-based analyses of topic frequency: when do I post, and what do I post about?
  • # of posts that contain links or retweets (a measure of how much I share information vs. generate original content)
  • where do I post from? (mobile vs desktop client)
Another data source that might be amusing to examine would be an extract of one's Facebook statuses (there are numerous applications out there that purportedly allow you to export statuses).

Final comment
While I'm not sure if I learned anything novel from this exercise, it's still useful to see that the data confirms the internal projection of how I see myself. I  believe self-awareness is one of the keys to maturity and personal satisfaction. Try it on your own feed -- do the results surprise you?