Sentiment Analysis engines in the Veritone cognitive engine ecosystem discern the tone behind a series of written words, which helps you gain an understanding of the attitudes, opinions, and emotions expressed.
These engines classify text according to sentiment or emotion, which depending on the engine, can be a score representing the overall negative, positive, or neutral sentiment for the file and by sentence, or can include a wider breadth of tags such as “happy” or “excited.”
Process text files in near real-time for use cases requiring a determination of emotion for fast analysis at scale via GraphQL API and Veritone Textbox UI.
Extract short-form or long-form text in files.
Deploy in a new or integrate into an existing application in the cloud via aiWARE GraphQL APIs, or with a subset that can be deployed on-premise via a Docker container. Learn more.
Leverage advanced sentiment analysis machine learning algorithms from the Veritone managed cognitive engine ecosystem– including algorithms from Veritone, niche providers, and industry giants.