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March 01, 2006

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Niall Cook

Matthew, you hit on the single biggest problem in automated sentiment monitoring - the fact that sentiment is relative to the views of the reader. What is good news for one person/company/country may be bad news for another. So how can an automated system ever get it right?

Matthew Hurst

Niall - I'm not sure this is the biggest problem. I suspect that the real issue is how you interpret and report the results. If I read 'I liked Super Size Me', the author expresses the appreciation of the movie. To McDonalds, the company being criticised, this is not a good thing. However, by reporting the number of people who like the movie (positive sentiment), they can judge the *negative* impact to their brand.

The other aspect of mining textual data for emotional content (affect analysis) aims to capture the emotional state of the author - this is actually easier to do independent of the pov problem.

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