As I have tried to argue in previous posts on this blog, digital media are enabling the emergence of an online public sphere (or spheres) where issues related to the EU are debated across national and linguistic borders.
But how can we make sense of the tangled mass of conversations that are taking place on different platforms? I think that social network analysis is one technique that can offer some potentially interesting insights.
I was introduced to social network analysis during my Fellowship at the University of Washington earlier this year. Lance Bennett’s class on the Politics of Digital Media touched on network theory, including Yochai Benkler’s seminal work The Wealth of Networks, as well as practical applications of social network analysis to protest movements from the Arab Spring to Occupy Wall Street. I was also impressed by the work that Katy Pearce is doing at the University of Washington using network theory to analyze the political communication landscape in the Caucusus (her “adventures in research” are documented on Katy’s blog).
In order to get a better grasp of social network theory and to see how we might use it to analyze the EU digital public sphere, I invested some time studying the literature, experimenting with tools like Nodexl and Gephi, and following an excellent Social Network Analysis MOOC (Massive Open Online Course) taught by Lada Ademic from the University of Michigan.
But, after a while, I have to confess that I ended up feeling frustrated and confused. The material and the tools that I found were too complex, and I was bewildered by the huge range of different parameters and mathematical formulae. I just wanted to create simple visualizations of social networks that I could understand easily, and that could be used as a basis for analysis and strategic communication decisions.
Then my colleague, Marco Ricorda, from the Commission’s social media team, introduced me to Bluenod (“a simple way to visualize and organize your communities”). The developers at Bluenod have done a great job producing a simple interface that allows users to create social network maps using any Twitter hashtag or username.
I used our recent “Telling the Story” conference for EU communicators to test Bluenod. The #ttsEU hashtag we used for the event generated a map of 1353 tweets from 140 users. I can only include a screenshot of the map in this blog, because WordPress does not accept the embed code generated by Bluenod, but you can access the interactive version of the network map here.
The map clearly shows who were the most connected participants in the online conversation (larger nodes = more connected). It helps to identify different subgroups in the conversation (interesting for an event like this one, which brought together representatives of different communities – regional policy, agricultural policy, employment and social policy, fisheries and maritime policy …). The visualization from Bluenod also shows the most popular hashtags that were used together with the #ttsEU hashtag, as well as a handy grid with images of the people who participated in the online conversation linking to their Twitter profiles.
Bluenod provides a useful complement to quantitative analytics tools like Topsy. For those of us who are interested in understanding and participating in the EU digital public sphere(s), social network analysis offers a useful way to identify key influencers and map different communities. I can see plenty of practical applications (for example, topical hashtags like #ttip and #ep2014 produce interesting results).