Multilingual sentiment analysis of texts from different sources (blogs, social networks,...). Besides polarity at sentence and global level, Sentiment Analysis uses advanced natural language processing techniques to also detect the polarity associated to both entities and concepts in the text. Sentiment Analysis also gives the user the possibility of detecting the polarity of user-defined entities and concepts, making the service a flexible tool applicable to any kind of scenario. Additionally, Sentiment Analysis detects if the text processed is subjective or objective and if it contains irony marks [beta], both at global and sentence level, giving the user additional information about the reliability of the polarity obtained from the sentiment analysis.
API AI provides a way to create mapping between language structures that are common in natural languesgea and data structures that are easy for software to parse and take action. Once these mappings have been created, you can make a query with either natural languages text or a voice sound file, and API.AI will return structured data with an action to take the parameters to act upon.