Aggressively probing Twitter habits

This repository has been closed for various reasons. You can read about it here.

You can still read this for your own interest and if you get some ideas do let me know. 🙂

What started as a simple idea to create an archive of my tweets turned out to yield something better. Yes, its kind of stupid and bad that Twitter doesn’t allow you to retrieve anything more than 3200 tweets. So its always good to have a backup of all the tweets that I have. After all my tweets can reveal valuable information about how I have changed overtime. Did I tweet funny stuff before more than now, or I do more retweets? Or am I a socially interactive guy who replies to other’s tweets? If have an archive I can always go back in time and look up what my tweets used to be!

So I wrote myself a simple Python script and archived my tweets as a Git repository. The script and instructions to do that that are available in this gist, so you can also do the same. Then I happened to post this repository on Github here. Things are all cool till here. You know you got an archive and you can do a time travel to look at your old tweets.

So next I waited for a few days and came back to see my archive online on Github and I found this.

Github had generated nice and beautiful graph of my Twitter activity over the weeks. Now as simple as it might look it actually it can give quite some useful stats. Initially when I joined Twitter I posted some tweets, indicated by the small blue lines. Then Twitter did not catch on me, and I gave it up. Quite some weeks later I make a comeback on Twitter and start tweeting regularly. There my activity line is soaring high in the last few weeks. Even more interesting are the dips in the graph. Maybe I tweeted less that week because I had exams or I was out on a holiday.

Even better is when you look at the following graph generated by Github.

I got this graph for the week starting 24th July. The above part shows that week’s activity level and below I get the number of tweets I made each day of that week. This is kind of awesome and I can see how much of tweeting I did each day. Sunday I was kind of more “active” on Twitter, and after that activity was pretty low. It is not surprising to see such a high level on Wednesday, I tweeted a lot while watching the live broadcast on Google I/O 2012. Its cool to know how the Twitter activity can correlate nicely with what activity I have been doing on that day.

You can see this graph live here.

Guess what? I can even analyse at what time of day I have been using Twitter throughout the week!

Here the bigger dots show I have tweeted more in that time slot, than the ones with smaller dots. It is kind of rad as I can easily map this to my daily habits. Sundays being a holiday means I am online in the afternoon hence, the bigger dots between 12pm to 2pm slot. It is also not surprising to see bigger dots late at night, I am online at at night generally, and tweet more during that time. Sparse small dots here and there throughout the day means that I do tweet or reply to tweets now and then in the day. There is almost no dot in the 2am to 6am time slot! Obviously I am sleeping at that time (well hopefully)!

You can see this graph live here.

Isn’t it just amazing how simply you are able to map your Twitter activity to your day to day lifestyle and how differing levels of activity can map to the important events that happen in your life? I was kind of fascinated to see these stats laid out visually right in front of me like this. This just scratches the surface different kind of analysis about your life or an event you can do with Twitter. For example it would always be possible to analyse my tweets to see I post more or just reply or retweet more. I can even figure out when I was happy and when I was angry from the tweets itself.


4 thoughts on “Aggressively probing Twitter habits

    1. Don’t worry, there won’t be overheating! You just download a copy of your tweets! The rest of the processing goes on in Github’s servers! 😉

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