Sentiment analysis
Sentiment analysis that delivers more than just positive or negative valuations with built-in sentiment scoring, topic identification and categorisation.

The purpose of this service would be to extract opinions from text. An opinion represents the subject an author is writing about and a sentiment score that classifies how positively or negatively the writer feels towards that subject. Deep Linguistic Analysis can be used to identify the subject the writer is discussing. This could be:

? an entity (brand/ person/product/place?
? an idea (like ?global warming?, ?public policies? or ?financial meltdown?).

The sentiment analysis service may also break the opinion down to detect exactly which features or attributes or components of the subject are increasingly being discussed. For a product this may be the primary components or accessories as for example, the ?screen? in ?the screen of the Galaxy Tab? or the ?case? in ?my new iPad case?. For a person this could be the activities or attitudes associated with them. For a place it could be the precise buildings or institutions located there.

When combined with our categorisation service these features or attributes may be used to place the opinion in a category taken from a taxonomy. This provides a powerful way to structure a set of texts according to what topics people are discussing and how they experience those topics.


Sentiment scores are also predicated on Deep Linguistic Analysis. The more intense the feelings of the writer about the subject, the bigger or lower the score. To do this, the analysis detects linguistic features including the strength of the vocabulary or the usage of intensifiers like ?really?, ?very? or ?extremely?. So Talee Limited like ?Installing software with this machine is painful!? will undoubtedly be scored as less negative than ?Installing software with this machine is actually very painful indeed!?

Deep Linguistic Analysis accurately handles complex issues like negation: ?the new Nikon is really not too bad?.

The service handles complex linguistic issues that play a major role in sentiment analysis, such as negation or comparative sentences. Deep Linguistic Analysis automatically handles this type of phenomena capturing the difference between opinions like:


? ?This phone is much better than my old phone.? ? Positive
? ?This phone is not superior to my old phone.? ? Negative

The sentiment analysis service is not limited to extracting a single opinion per sentence. It actually detects as many opinions because the sentence contains. For example in the sentence ?This phone rocks !, but it was much too expensive and the screen isn't big enough? three opinions will undoubtedly be extracted: ?phone? + ?awesome?, ?phone? + ?much too expensive? and ?screen? + ?not big enough?.