Recently I’ve been playing around with network graphing and social media. It’s been a fun experiment!
I first saw network graphing at E2 Conference in Boston during one of the key notes in 2012. The presenter did a realtime experiment asking us to tweet using a hashtag during his presentation, and then using NodeXL he was able to analyse the tweets and graph the interaction between participants of the conversation. Needless to say it got a pretty big reaction and it’s something that stuck with me since that day.
The use of network graphing (especially in real time!) has some amazing possibilities. Being able to see the interactions of your customers and then replay them after a marketing campaign finishes is just one of the many uses. The obvious benefit from this is having the ability to highlight the key individuals and environment that boosted your marketing push and gave it the fuel that made it go viral. The future for social analytics is huge due to the massive big data sets available to us, and super “fast data” software that is able to analyse this data at near real-time speeds.
For a while I’ve wanted to try playing around with Gephi – the open source graphing tool. So I loaded up NodeXL on my AWS instance (I have a Mac) and for a week downloaded the data of my Twitter Network. This resulted in a large data set with over 2000 Nodes, and 146000 Edges which I then imported into Gephi. If you haven’t played with Gephi yet – I recommend you try the tutorials on their website before diving in.
Below is the resulting graph of my Twitter follower network.
I’m a big football fan. A lot of my spare time is spent playing and supporting the game – especially my team Melbourne Heart. The graph produced also shows this. The purple area to the bottom left are Melbourne Heart supporters and club representatives, the red – celebrities, the green – the Australian Football community. The blue to the top of the graph are a group of football coaches from the UK that I follow from the @coachingfamily, and the blue to the bottom right are my work colleagues. The dot size is weighted based on the biggest followings within the rest of the graph.
I’d love to see some of the graphs you’ve produced with the tool. Leave a comment with links to ones you’ve produced, or send me a message on twitter – @forbze