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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 is 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 author feels towards that subject. Deep Linguistic Analysis is used to identify the subject the author is discussing. This can be:

  • an entity (brand/ person/product/place…
  • a concept (like “global warming”, “public policies” or “financial crisis”).

The sentiment analysis service will also break the opinion down to detect exactly which features or attributes or elements of the subject are being discussed. For a product this could be the main 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 specific buildings or institutions located there.

When combined 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 set of texts according to what topics people are discussing and how they feel about those topics.

Sentiment scores are also based 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 be scored as less negative than “Installing software on this machine is really very painful indeed!”

Deep Linguistic Analysis accurately handles complex issues like negation: “the new Nikon is really not bad at all”.

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 much better than my old phone.” – Negative

The sentiment analysis service is not 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 much too expensive and the screen is not big enough” three opinions will be extracted: “phone” + “awesome”, “phone”“much too expensive” and “screen” + “not big enough”.

 

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