Over the course of the General Election I recorded 1000 random tweets every hour and sent them to tweetsentiments.com for sentiment analysis.

Tweetsentiment have a service which gives one of three values to each tweet. ‘0’ means a negative sentiment (unhappy tweet), ‘2’ a neutral or undetermined sentiment and ‘4’ positive (happy tweet). Similar technology is used to detect levels of customer satisfaction at call centres by monitoring phone calls.

Obviously it’s difficult for a machine to detect the emotional meaning of a sentence, especially with the strange conventions used on Twitter. Despite this Tweetsentiment seems to be fairly reliable – tweets always which express happy emotions tend to be rated as such, and vice verse. More accurately, if Tweetsentiment does make a classification it tends to get it right. Sometimes an obviously positive / negative tweet gets a ‘2’, but that shouldn’t affect things here.

My hypothesis was that the Twitterati would be less happy if there was a Conservative victory. Of course I can’t prove that Twitter has a bias to the left, but I would presume that young, techy, early adopters are more likely to be left leaning. The reaction to the Jan Moir Stephen Gately article perhaps supports this.

David Cameron famously noted that Twitter is for twats, I wondered if Twitter would reciprocate…

Media_http1bpblogspot_uonky

The graph indicates that usually Twitter is just slightly positive, with a mood value of 2.1 on average. As predicted, as a conservative victory becomes apparent on Thursday evening there is a decline in mood which lasts until Saturday lunchtime. Then everyone cheers up, presumably goes down the pub, and is pretty chirpy for Sunday lunch. Sentiment only returns to average for the beginning of work on Monday morning.

In short, it does look like the election result was a disappointment to Twitter.

Obviously we need to know what normal Twitter behaviour is over the course of the week to draw very much information from the graph, and this is something that I’m going to try and produce a graph for soon.

It does look as though the size of negative reaction to a once-a-decade change in government is about the same magnitude as the positive mood elicited by the prospect of Sunday lunch – which I think is fairly consistent with the vicissitudes of Twitter as I experienced them.

I used Twitter’s API to gather the data, and frankly, it’s not particularly great, particularly if you want to get Tweets from the past. I was surprised to discover that any Tweets more than about 24 hours old simply disappear from the search function on Twitter.com – in effect they only exist in public for a day. For this reason the hourly sample size wasn’t always exactly 1000, but it was on average.

I’ll post again when I have some more data on normal behaviour. I’m also curious to find out if different countries have different average happiness levels on Twitter, but I think finding a Tweetsentiment-style service for other languages might prove difficult.

Leave a reply

<a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong> 

required