Swarm Creativity Blog

Today I checked on the mood of the US Population through Twitter, using Twitter’s Geotagging feature. Alan Mislove from Northeastern had already found that the mood of the nation changes over the course of the day, with people having a low over lunch, and getting collectively happier in the evening, when work is over. Using our Twitter-collector-tool built into Condor , I was able to easily replicate this result. I counted the number of retweets about “hope”, “fear”, and “worry” in the major population centers of the US, by collecting the tweets at four 2000 kilometers circles with centers at Pittburgh (North East), Atlanta (South East) Las Vegas (South West), and Boise (North West). (see picture below) I then constructed the social network between the retweeters as described in a previous blog post . The way it is calculated, it also factors in the importance of the retweeters, where a link is drawn between two people if a person retweets a post from the other person. The picture abo...

Yesterday November 2nd 2010 was midterm election day in the US. I was curious what Twitter would tell us about the mood of the voters. It was already clear that things did not look good for the Democrats. In prior work analyzing data from 2009 we had already found that monitoring posts for the occurrence of “hope”, “happy”, “fear”, and “worry” would give us a good proxy for the mood of the population, particularly if we focused on the retweeted posts. So this time I repeatedly ran our Twitter data collector in 30 minute intervals, each time collecting the 200 most retweeted Tweets containing either hope, happy, fear, or worry. The picture below shows all tweets, with the red dots depicting the tweets containing more than one of the search words. Measuring the betweenness value (i.e. the importance of the search term) shows that popular tweeters prefer tweeting about “happy” (32%) and “hope” (30%) over the “worry” (19%) and “fear” (19%) tweets. Note that I collected precisely the sam...