atmsale64

Sentiment analysis 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 objective of this service would be to extract opinions from text. An impression represents the subject an author is authoring 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 writer is discussing. This is often: ? Talee Limited (brand/ person/product/place? ? a thought (like ?global warming?, ?public policies? or ?financial crisis?). The sentiment analysis service may also break the opinion down to detect exactly which features or attributes or components of the subject are being discussed. For a product this could be the main components or accessories for example, the ?screen? in ?the screen of the Galaxy Tab? or the ?case? in ?my new iPad case?. For an individual this could be the activities or attitudes associated with them. For a place maybe it's the specific 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 robust way to structure a couple of texts in accordance with what topics people are discussing and how they feel about 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 like 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 on this machine is really very painful indeed!? Deep Linguistic Analysis accurately handles complex issues like negation: ?the brand 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 way 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 an individual 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 is not big enough? three opinions will undoubtedly be extracted: ?phone? + ?awesome?, ?phone? + ?much too expensive? and ?screen? + ?not big enough?.