Know your Twitter community and prioritize who to have a conversation with is sometimes challenging. Thanks to scripts from Amit Agarwal and Martin Hawskey, it’s now easy to get more insights about your community. Inspired by their work, I created a simple graph to express a Twitter community network graph. With these kind of graphs you can find out who is talking about you or your company, so you can start prioritizing tweeps. I.e. you can start bridging gaps and connect to tweeps that are not in your direct network.
Let’s take PrioTime as an example. PrioTime is an app that helps you to get the most out of your life. Besides they run a blog and among various social media channels, they author @PrioTime. The data set for this example contains tweets about PrioTime collected since 14/08/2014.
PrioTime Twitter Community Network Graph
This network graph displays the connections between the various tweeps. The source node has been defined based on the tweep. The target node refers to the first mentioned tweep (this could also be a location).
The size of the nodes displays the degree of the tweep and its Klout score. This Klout score is dynamic and will change over time. You can increase and decrease the number of visible nodes by clicking on the small arrows left on top of the graph.
Priotime Twitter Community Top-10 Tweeps based on Klout score
This chart displays the Top-10 Tweeps according to their average Klout score. As this Klout score is dynamic, it will change over time. More about Klout score can be read here.
PrioTime Twitter Community Top-10 Tweeps
This chart displays the Top-10 Tweeps, based on the amount of tweets they produced during the selected period. As you can see, PrioTime itself it publishing the most.
PrioTime Twitter Community Top-10 Amount of Followers per Tweep
This chart displays the Top-10 of the average amount of followers per tweep during the selected period.
Now this graph has its limitations: the target is based on the first tweep that is encountered in the tweet text, so even when there are more mentions in the text, only the first one will appear. Besides, Google docs have a limitation to 400.000 cells per document, so if you would like to analyze a popular hashtag or query, you will run out of space.