This morning, I led an hour of WebShop 2012. At the beginning of the talk, I asked the audience, especially students, to brainstorm questions about public officials and Twitter, specifically. You can see the list we generated as a Google doc. Many of those questions my colleagues and I are already investigating, but like I said this morning, we can’t do it all. That list alone will keep me busy for a long, long time. One question that did come up both last night and this morning was about how polarized or divided the conversation is. So, last night, I processed some hashtag data from my public officials on social media project so we could investigate.
Towards the end of the talk, I used that hashtag data as a live demo to show my work process and luckily, Bernie Hogan, Marc Smith, Ben Schneiderman, and others jumped in with ideas for this very graph. Without their input, it would have been hard for me to demonstrate how social and contentious analyzing this data is.
To get this graph, I downloaded the raw JSON of tweets by members of Congress from Twitter’s streaming API, parsed it into a normalized MySQL database, and then queried to pull just hashtags and the users who posted them. I used UCINet to transform that two-mode tweeter-hashtag network into a one-mode tweeter network and imported that one-mode network into NodeXL. That means each tie exists because those two tweeters used the same hashtag. I used some existing data about the followers, friends, tweets, chamber of Congress, political party, sex, and state they represent as attributes for each member of Congress. The timeframe for these tweets is December 22, 2011 – March 15, 2012.
Marc predicted that we’d see a partisan divide. What do you think? Take to the comments to tell me what you see (or what you’d like to see in a new graph)!