Take a look at below:
Deep Linguistic Analysis for Topic-level Analysis
Bitext’s API uses Deep Linguistic Analysis based on grammars, which allows for opinion analysis not only at the sentence level, but also at the phrase level within the sentence. This is possible because the syntactic analysis identifies the different phrases (noun phrases, adjective phrases, verb phrases etc) and their dependencies.
The sentiment analysis service is not limited to extracting a single opinion per sentence. It can actually detect 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”.
The service can therefore perform topic detection:
an entity (brand/person/product/place…)
a concept (like “global warming”, “public policies” or “financial crisis”).
and detect exactly which features or attributes of the topic are being discussed.
Deep Linguistic Analysis accurately handles complex structures like negation: “their new camera is really not bad at all”.
The sentiment analysis service handles complex language structures which play a major role in sentiment analysis, such as negation or comparative sentences. Deep Linguistic Analysis automatically handles these structures and can capture 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
AlchemyAPI helps developers and businesses build cognitive applications through text analysis and deep learning.