Sometimes I get caught up in coding something totally inspired by another project. It not only gives me an excuse to continue to program but also be flexible and create tools that add value to the university.
Today, 37 Signals announced they would start publicly displaying their “Smile Ratings”. This got me thinking, we rate all our twitter mentions as “Happy”, “Indifferent” and “Sad” in the same way, why not display that information similarly.
So I took an hour and this is what I came up with:
What it shows us
I created an initial version that included “indifferent” tweets but there were far too many (we get a mentioned ~9 minutes/24 hours per day) to make the graph useful. So limiting it “happy” and “sad” made sense since those are the only reactions that matters.
As you can see >60% of the tweets are sad and that makes us sad. 🙁 But we like to look at it as an opportunity to change opinions. We reply to (almost) all negative tweets to answer questions, help students, break misconceptions and gather information. We also pass all information along to the respective departments to follow up and make long term changes when necessary.
With this data we plan to continuously evaluate our work on a daily basis, hopefully start graphing the happy/sad ratio over time. The next step is to build upon these relationships in order to assign an overall satisfaction value. Of course the initial negative comment cannot be taken back but if we end up fixing the issue the resolution usually results in a happy tweet from the student to all of their followers. So where does that tweet sit compared to someone who is just complaining with no real solution to their problem?
In the end public tweets are out of our control, people will say what they will when they want. All we can do is monitor and respond. At least now we have another way to monitor our progress.
The tool above is currently only available internally and we “borrowed” the smile and frown images right from 37 Signals. Sorry guys, we just love you so much! (Don’t worry, if we ever make it public we will totally use our own faces)