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Who influences the influencers? Visualising Twitter
Wednesday, 22nd February 2012
Visualising Twitter networks is one way to help verify social media sources and pull presentable data out of the noise. But how do you go about doing it? Sam Martin has written up a great case study to help you learn.
One of the biggest issues to face the information industry with the rise of social media is how much value you can place on intelligence gathered from public services like Twitter, Facebook or LinkedIn. Obviously there are variations between platforms – a professional profile on LinkedIn is likely to be a more complete and reliable picture of a user than an avatar image and a 140 character bio on Twitter.
Storyful is a social media curation service that is trying to tackle the problem. It originally started as a user-facing service trying to source and encourage citizen journalism, but soon realised that selling its expertise to other businesses was an opportunity. I recently saw Markham Nolan talk about how they do it and I thought there were a few interesting points – not least of which was the question "who influences the influencers?"
When trying to cover civil unrest in Egypt, they had wanted to pick out the key people relaying reliable information out of the country. They had used the technique of visualisation. By putting tweets about Egypt through a tool, they were able to pick out the key influencers – the people who had the most retweets and who generated the most followers. They could then safely assume that these were sources trusted by the majority of the people on the ground. They took this a little further, however, and analysed who those people trusted. This led Storyful to people who were excellent primary sources for information.
If the idea of a Twitter visualisation tool worries you – then don't fret. There are plenty available on the web, and some useful guides on how to get the best out of them. Garin Kilpatrick lists 10 of them on the Twitter Tools Book website.
"Great, but what do I do with that data?" I hear you ask. Well, Sam Martin has provided a very detailed example of what he did with one set of data. The topic may be a little trivial – the uproar that continues to surround the England football team captain – but this is a great resource if you want a tutorial on how to turn Twitter data into something you can present. Sam is a CAST MSc Digital Sociology student at Goldsmiths College, and you can find his blog post at “Visualising Twitter Networks: John Terry Captaincy Controversy”.
By Martin Belam
Martin Belam is Information Architect for guardian.co.uk. Before joining The Guardian, he worked as an Internet Consultant with organisations like the BBC, Sony, Vodafone and the Science Museum.
Martin also blogs about information architecture and the media at currybet.net and can be found on Twitter as @currybet.
Martin can be reached at email@example.com
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