Swarm Creativity Blog

We did some more coolhunting on Twitter over the last few days to check out if the negative advertising blitz against Newt Gingrich that Mitt Romney is running right now in Florida has any impact on the Twittersphere. The answer is “Yes, by all means”, which explains why even in the Romney tweets Gingrich is the most prominent word in the term view, and Gingrich is much more central among twitterers than Romney in the combined Romney-Gingrich view in Florida. To measure that, we collected 4 twitter maps: 1. All the tweets in the US about Gingrich and Romney: As we can see, the twitterers about Gingrich tweet more, and they are also more important. The purple lines are the retweet network containing the words “gingrich” or “romney”. 2. All the tweets in Florida about Gingrich and Romney: In Florida, few people tweet about Romney compared to Gingrich. But let’s now look at what these people tweet about, when they tweet about Gingrich in Florida: This picture has been computed using Condo...

Today (11/20/11) I ran a Condor twitter analysis for #ows (the Occupy Wallstreet Twitter tag) and #teaparty (the Tea Party Twitter tag), trying to predict public sentiment for these two social movements. I only collected retweets, and constructed the retweet-network, measuring the importance of people retweeting based on their social network position. The picture below shows the resulting network, each dot is a twitterer, each line is one or more retweets. Surprisingly we get three clear clusters, a Occupy Wallstreet cluster (blue, at the bottom), a Tea Party cluster (yellow, in the center) and a mixed cluster at the top. Red dots are people tweeting both about #ows and #teaparty. A closer look at these three clusters tells us that the blue cluster is Occupy Wallstreet sympathizers talking about issues near and dear to them, the yellow cluster is Tea-Party sympathizers doing the same about their cause, while the mixed cluster at the top consists of Occupy Wallstreet sympathizers badmou...

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...