Who influences the influencers? Visualising Twitter
Jinfo Blog
22nd February 2012
By Martin Belam
Abstract
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.
Item
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”.
- Blog post title: Who influences the influencers? Visualising Twitter
- Link to this page
- View printable version
- Building a rapport with LinkedIn
Monday, 13th February 2012 - Strategic use of social media - Heron & Hughes at news:rewired
Wednesday, 8th February 2012 - Social media and the emergency services: Part 2 - Emergency management
Tuesday, 3rd January 2012 - Social media and the emergency services: Part 1 - Policing in your pocket
Thursday, 1st December 2011 - LinkedIn: An awesome information resource for building your reputation, your connections and your knowledge [ABSTRACT]
Wednesday, 1st June 2011 - Data Visualisation: Tools and Examples [ABSTRACT]
Monday, 9th February 2009
Discussing news and AI strategies with the Financial Times
Community session
21st November 2024
2025 strategic planning; evaluating research reports; The Financial Times, news and AI
Blog posting
5th November 2024
November 2024 Update
YouTube video
7th November 2024
- 2025 strategic planning; evaluating research reports; The Financial Times, news and AI
5th November 2024 - All recent Jinfo Subscription content
31st October 2024 - End-user training best practice research
24th October 2024
- Jinfo Community session (TBC) (Community) 11th December 2024
- Discussing news and AI strategies with the Financial Times (Community) 21st November 2024
- Asia-Pacific Community session (Community) 19th November 2024