Happy New Year! Play with Data

Happy New Year!

My latest feat in data visualization is an interactive graphic of #MySciBlog social network analysis of blogs read regularly by science bloggers.

You can play with the interactive data here: http://bit.ly/MySciBlogRead 

Just a reminder for those taking a look at this visualization: this is exploratory data. The network is most likely far from complete, as every blogger who participated in my survey was allowed to only list a maximum of three other science blogs that he/she reads regularly. However, many bloggers probably read far more than 3 other science blogs, or blogs in general, on a regular basis. This means that any apparent isolation of particular blogs or groups of blogs in my visualization could be an artifact of incomplete sampling (a good number of bloggers represented by blog nodes in this graphic didn't actually take my survey) or an incomplete listing of all the science blogs that any given blogger reads on a regular basis.

However, I think the data is still useful, especially for my purpose of looking for prominent "read" relationships between blogs and whether these relationships translate into shared practices. I am especially interested in looking into mutual ties in this network graphic, i.e. cases where two or more bloggers mutually list each other's blogs as ones they read on a regular basis. If I read your blog and you read mine, there may be a greater chance that we will swap blogging practices, share content norms, respond to each other's posts, etc. I may like the way you format your posts, or the way your posts read, and naturally adopt some of your practices, and vice versa. Or, we may both read each other's blogs in the first place because we have similar interests or tastes in science blogging, which also leads us to share blogging practices.

Another note - I've included in this graphic all the blogs listed by survey participants as "science blogs" that they read on a regular basis. Meaning, I did not go into the data post-collection to remove blogs that might not be widely agreed upon as "science" blogs. I asked survey participants to list up to the top 3 other "science blogs" that they read on a regular basis, and I let the responses stand on their own in this graphic. This may be a limitation of my procedure, but in my mind it is better than me imposing my own definition of what constitutes a "science" blog onto this data.

 

Note: I filtered my Gephi network map by the 'giant component', meaning that a small percentage of completely isolated blogs are not visible in the graphic.