Sentiment analysis

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

The purpose of this service is to extract opinions from text. An impression 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 is used to identify the subject the author is discussing. This is often:

? an entity (brand/ person/product/place?
? a thought (like ?global warming?, ?public policies? or ?financial crisis?).

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

When coupled with our categorisation service these features or attributes can be used to place the opinion in a category taken from a taxonomy. This provides a powerful way to structure a couple of texts in accordance with what topics folks are discussing and how they experience those topics.


Sentiment scores are also predicated on Deep Linguistic Analysis. The more intense the feelings of the author about the subject, the higher or lower the score. To achieve this, the analysis detects linguistic features such as the strength of the vocabulary or the use of intensifiers like ?really?, ?very? or ?extremely?. So a comment like ?Installing software on this machine is painful!? will undoubtedly be scored as less negative than ?Installing software with this machine is really 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 significant role in sentiment analysis, such as for example negation or comparative sentences. Deep Linguistic Analysis automatically handles this sort of phenomena capturing the difference between opinions like:


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

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

They posted on the same topic