Linguistic Analysis Shows Shift in Support for Party Leaders and Winner Per Topic

CAMBRIDGE, United Kingdom--(BUSINESS WIRE)-- Linguamatics, a leader in enterprise text mining, today announced a new view on the instant reactions made on Twitter about party leaders during the second televised UK 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 party leader

For the second debate the twitterers indicated that their top 3 issues were Europe, immigration, and religion, including the discussion on the Pope’s visit. The second debate covered a wider variety of topics than the first and so the tweets are more widely spread. Cameron won narrowly on Europe, Clegg on immigration as for the first debate, and Brown on religion (Figure 2). However, the combined analysis of winner per topic shows that Clegg has maintained his lead (Figure 3), as he does for the debate as a whole (Figure 1).

Figure 2 – Winner per topic from number of relevant positive tweets

Figure 3 – Percentage of specific topics won by each leader

Linguamatics’ linguistic analysis of the debate transcript itself (Figure 4) shows that, in the second debate, Europe dominated the leaders’ discussion. The twitterers talked more about immigration than the leaders relative to the other topics (Figure 2).

Figure 4 – Number of times a topic is mentioned per leader

Linguamatics’ I2E text mining software was used to find and summarize tweets that have the same meaning, however they are worded. I2E identifies the range of vocabulary used in tweets and uses linguistic analysis to collect and summarize the different ways opinion is expressed.

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Linguamatics helps organizations to maximize the value derived from information resources through effective deployment of innovative natural language processing (NLP) based technology. The versatile interactive information extraction system, I2E, helps organizations to do much more than simply cope with vast quantities of information. Its unique combination of search and text mining enables organizations to turn this information into a competitive advantage. From life sciences and healthcare to business intelligence, from media analysis to security, users mine large collections of documents, extracting relevant facts, relationships and quantitative data from content such as scientific papers, news feeds, patents, or internal reports. Linguamatics has a rapidly growing user community with I2E deployed at most top-10 pharma companies. The company was founded in 2001, and is headquartered in Cambridge, UK with US operations in Newton, MA, USA.

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CONTACT:

Linguamatics Ltd
Judith Bandy
Tel: +44 (0)7912 944385
Email: judith.bandy@linguamatics.com
www.linguamatics.com

KEYWORDS:   United Kingdom  Europe

INDUSTRY KEYWORDS:   Entertainment  Technology  Internet  Telecommunications  Public Policy/Government  Other Government  Mobile/Wireless  Blogging  Social Media  Communications  Other Communications  Mobile Entertainment

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