Monitoring Midterm Election Night Through Twitter Buzz

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 same amount of tweets for each search term (24*2*200), but then constructed the social network of the tweeters based on who retweeted whom’s post. To illustrate the point, the picture below only shows the social network (without drawing the links of the tweets to the search terms – these links were used in the first picture to calculate betweenness.)

As this picture shows, the tweeters about hope and happiness (yellow and light brown) are mixed in the center, while the tweeters about fear (blue) and worry (green) keep mostly to themselves in the periphery. So even in the Tweetersphere, happy people connect, while worriers stay put at the borders of the tweeter-network.

Here is the picture analyzing the contents of all tweets I collected containing the term "fear", displaying the semantic network of the most important terms about fear:

As the picture shows, Democrats are on the losing side, Republicans won, but the term "republican" is close to the term "jobless", so fear about continuing joblessness was the main cause for their win. Harry Reid’s win is also predicted by Twitter - the terms "Reid" and "Nevada" are connected to "won".

Now the picture with worry:


It shows Republicans worrying about a potential victory of Joe Sestak in Pennsylvania (which did not happen), Tea party members worrying about the loyalty of John Boehner, moms happy they don’t have to worry about their health care thanks to Barack Obama, and somebody worrying about loosing his Facebook account.

And here is the term view for “hope”:

It seems Justin Bieber and Harry Reid from Nevada share the stage of hope, with some tweets about the elections in California thrown in. Adam Lambert’s Halloween discussion of his costume is picked up by his fans. Barack Obama still draws lots of emotions and inspires hope among some tweeters.

Finally the concept network for “happy” showing a quite different picture:

The top tweets containing “happy” are not about the elections – these elections are nothing to be happy about according to Twitter - but are by young girls, talking about their moms, and Justin Bieber. It is interesting that the term “happy” does not even show centrally in the term network.Rather, the discussion is about things that make these girls, who are mostly not even from the US but from Asia, happy, like love, and surprisingly, their moms, and it seems, eating a Burger at MacDonald’s in San Francisco.
The only election tweets are by girls rejoicing that voting is finally over, so they don’t get the weird calls at their doors by election workers anymore.