AI Text Entity Sentiment Analysis API

What it does

Entity Sentiment Analysis helps you send text and get entity-level sentiment results back through the Google service. It is built for cases where you need to know not just whether text is positive or negative, but how sentiment is attached to specific entities mentioned in that text.

Send a request body with text and requested_service, and optionally include language, encoding, and a google object with key and google_language. The input is plain text, so you can analyze reviews, social posts, support tickets, news mentions, or survey responses without pre-structuring the content first.

The response returns a data object with a google field when requested_service is google. Because the schema is flexible there, treat it as the analysis payload for the text you sent. Use it when you need entity-aware sentiment signals for dashboards, moderation workflows, market research, or triaging feedback by brand, product, or person.

Entity Sentiment Analysis fits into pipelines where text classification alone is not enough. You can feed it short comments or longer passages and use the returned analysis to group mentions, detect sentiment around named entities, or enrich downstream reporting.