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| 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)
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?
