Monthly Archives: September 2012

While I was writing my book about Twitter (Twitter: Social Communication in the Twitter Age), I took an interest in tracking the US Republican primary as it was being constructed within Twitter. Last year, I started collecting all geo-located tweets  (tweets with location information turned on) for the 50 most populous urban American cities (according to U.S. Census statistics ). Because of the geographical richness of this data set, I thought it would be a perfect source to use to study twitter activity surrounding the US Republican primary. Working with  Alexander Gross and Stephanie Bond, I designed and developed a tool to visualize this specific geographically-anchored landscape.

The 2012 US presidential election provided another opportunity to leverage this data. Twitter has been extremely active in terms of election-related discourse. Our Election 2012 Twitter Visualization Tool uses emergent big data research methodologies to visualize the election. The visualization tool has been optimized for the Safari browser (and is known to have some issues in other browsers).

The goal of our research is to explore urban American responses to the 2012 presidential candidates on Twitter. In order to create a representative sample of tweets from urban centers in the United States, we collected tweets from Twitter by location. We took the 50 most populous American cities according to the U.S. Census and instructed Twitter to send us tweets that were within 7-12km of the locations of these cities.

Our software collects these geo-located tweets and uses the data to chart the relative buzz surrounding candidates in the 2012 presidential election. The tool charts the relative popularity of each primary candidate as measured by the number of tweets which we have collected over the last 24 hours and identified with a particular candidate. For a tweet to be counted as referring to a particular candidate, the tweet must contain the candidate’s first and last name separated by a space e.g. “Mitt Romney” or the candidate’s official campaign twitter account name or the account name eg @mittromney. A single mention as reported by the chart’s dynamic legend is equivalent to one tweet which contains one of the candidate names. Tweets which contain more than one candidate name will be counted as mentions for both candidates. These stringent rules prevent unecessary possible over counting of tweets for a candidate. Though the frequency of the tweet count in our visualization is low because of this, the data collected is very robust. Specifically, all tweets visualized do refer to Obama or Romney.

Please visit the tool’s webpage at my lab, the Social Network Innovation Lab, for more detailed information.