Linguistic analysis shows level of support for party leaders

Cambridge, UK-based Linguamatics has released the 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.
 
As per the analysis of the number of tweets showing positive sentiment towards each party leader, 65% of twitterers who expressed an opinion said that Nick Clegg performed best.
 
He was 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%.
 
The twitterati also indicated that their top five issues were health, immigration, economy, education and crime, with Cameron winning on health, Clegg on immigration and education, and Brown on economy and crime. However, the combined analysis of winner per topic showed that the leaders were more evenly split than for the debate as a whole. Linguamatics’ linguistic analysis of the debate transcript itself shows that the leaders talked about education most, followed by crime, health, tax and jobs, which revealed different priorities than for the twitterati.
 
The company says for Twitter, it has demonstrated an objective way to detect real world opinion as it develops.
 
“However, this ability to filter huge volumes of text in real time has implications for decision-makers across the board,” said John M. Brimacombe, executive chairman of Linguamatics.