Posts from April 2010

There is a new view on the instant reactions made on Twitter about party leaders during the second televised election debate, April 22 2010. Preliminary results are published of the linguistic analysis of 169,000 tweets sent by 38,986 twitterers from 8.00pm – 9.30pm on the night of the debate.

Updated results for the analysis of 211,000 tweets sent by 47,420 twitterers from 8.30pm – 10pm on the night of the first UK election debate, April 15 2010, are also presented.

The overall tweet analysis (Figure 1) shows that for the second debate 43% of twitterers who expressed an opinion said that Nick Clegg performed best, down from 57% in the first debate, followed by Gordon Brown (35%, up from 25%), and then David Cameron (22%, up from 18%).
 

Figure 1: number of tweets showing positive sentiment towards each other

The analysis identified tweets saying that a particular leader was doing well or made a good point, or that they like the leader, etc. Linguistic filtering removed examples which were about expectations, e.g. “I hope the leader will do well”, questions, such as “anyone think the leader is doing well?”, and negations, such as “the leader did not do well” or “the leader made no sense”.
 

Figure 2: winner per topic from number of relevant positive tweets


The results from a twitter analysis of the first UK election debate on April 15th between Gordon Brown, David Cameron and Nick Clegg are published below. We looked at what Tweeters were saying about the potential leaders and the topics they were speaking on.

Preliminary results of the linguistic analysis of 211,000 tweets sent by 47,420 twitterers from 8.30pm – 10pm on the night of the first UK election debate, April 15 2010. The overall tweet analysis (Figure 1) shows that 65% of twitterers who expressed an opinion said that Nick Clegg performed best, followed by Gordon Brown (21%), and then David Cameron (14%). In contrast, the immediate post-debate poll by Sun/YouGov put Clegg ahead at 51%, Cameron at 29%, and Brown at 19%.

Figure 1 shows the number of tweets that expressed a positive sentiment towards each of the party leaders.

The analysis identified tweets saying that a particular leader was doing well or made a good point, or that they like the leader, etc.

Linguistic filtering removed examples which were about expectations, e.g. “I hope the leader will do well”, questions, such as “anyone think the leader is doing well?”, and negations, such as “the leader did not do well” or “the leader made no sense”.