The Oxford-developed software is said to build on a thorough understanding of linguistics to assess accurately what people mean from what they say online.
TheySay’s approach of using linguistic intelligence along with machine-learning techniques is claimed to overcome limitations of existing sentiment analysis tools.
It is based on work by Prof Stephen Pulman and Karo Moilanen from Oxford University’s Department of Computer Science. The researchers used an exhaustive sentiment classification and scoring scheme to classify linguistic structures for sentiment and to score all individual entity mentions in text.
Prof Stephen Pulman said: ‘We have a very large database of words annotated by hand along several dimensions for the emotional meaning they carry, and we also evaluate the grammatical context in which these words occur, taking account of the effects of negation and other constructs that change meaning. A word such as “progress” is generally perceived as positive, but not when it is in a context such as “fail to progress”, or “little progress”.
‘By taking account of grammatical context we can determine emotional attitudes towards the entities and relations mentioned in a text.
‘Many companies are concerned about their reputation and the reception that their products receive in the marketplace. TheySay can be used to analyse news reports, blogs, or postings on Facebook or Twitter — companies can get almost instant feedback.’
Understanding sentiment is claimed to be a proven source of competitive advantage for businesses, government entities, public sector bodies, political organisations and individuals keen to monitor and measure what is being said about them on the internet.
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