Click the image to see the results of a project I've been working on for the last week. My goal was to start to get a handle on how well students in my Web Marketing Practicum class were getting on in Buzz. What I produced was a basic tabular report designed to show how well the students were connecting with each other and with external parties.
Here's how to read the columns:
- Participant: Just the class participant whose network is being examined. I'm included in this as I'm part of the network.
- Mutually Following: The people the participant is both following and being followed by. For many social network analysts, this column is what constitutes the social network. Other participants in the class are color coded orange and in a bold weight font. Those outside the class are blue and in a regular weight font. A quick perusal of this column reveals that, with the exception of myself, the majority of each of the other participant's networks is composed of other participants.
- Not Following Participant Back: Often, this column is not important. It may represent people who the participant is following purely for information. However, it can start to be an issue of poor perception management if no one the participant follows is following them back.
- Participant's Other Followers: These are people who follow the participant but are not followed by the participant. They may represent an opportunity for the participant.
I'm sure this analysis seems super simple. What's the upshot?
- One issue with Buzz as it stands in May, 2010 is that it does not have an easy way to perceive your network. Who's in? Who's out? Who are potential people to connect with. This analysis begins to provide an answer to all of those questions.
- Right now, I'm clearly the most connected node on this network by any measure. Students may be able to feed off of me. Also, some of them have started to grow their networks, and as they do so, they can feed off of each other.
My plan is to do a separate post on the Python code itself sometime in the next 10 days, and I'll include a cleaned up version of the code with that. Suffice it to say that I did not use the Python client libraries for the Buzz API. Rather, I just used the RESTful API. The main reason was that it was chock full of examples for how to get the data I wanted. I did wind up writing a simple Python abstraction layer for it.
To be honest, it may be seeing wether I can duplicate this effort with the twitter API. All reports indicate that my students may be having an easier time there. Tracking is certainly easier. I just created a list for my students.
However, even with twitter, figuring out who is in your active network is hard. As simple as this exercise is, it begins to accomplish that task.