Contact Us

our email: [email protected]

Corporations use NLP techniques to figure out how people feel and what they think, especially in the areas of semantics and figuring out what someone means. “Word sense disambiguation” in NLP means being able to figure out what a word means in a certain situation. Voice tagging and other NLP techniques are often used in social media to figure out things like the subject, verb, and object of a sentence. NLP-based sentiment analysis is then used to find an underlying relationship and figure out whether the tone of the sentiment is positive, neutral, or negative.

Text analytics tools provided by the Language Service can analyze labels and text to determine the sentiment of the text. It provides some context for the sentiment the author wanted to convey. This feature can find both good and bad feelings in online forums, customer reviews, and social media. The text is analyzed by the service using a machine learning classification model. It then gives the text a score between 0 and 1 based on how it makes the reader feel. Scores closer to 1 show a positive attitude. For scoring, the point in the middle of the range (0.5) is considered neutral or indecisive.