Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Detect emotion within content, such as fear, happiness, sadness, disgust, etc. It is able to process content in over 200+ languages. This classifier can instantly consume the content within a pipeline, optimize the content for speed and cost efficiency, and pass into LLM systems. Within the classifier, the LLM response is restructured, the post is augmented with the new metadata, and continues in the pipeline.
Drawing from over 1,000 Chinese news sources and over 25,000 English news sources, Socialgist provides a comprehensive overview of current events, editorial opinions, and journalistic analysis. This dataset is invaluable for understanding media narratives, tracking news cycles, and analyzing the impact of current events on public discourse and sentiment across various regions and topics.
How Datastreamer works
Quickly apply Datastreamer Emotion Detection Classifier to Socialgist News with a Datstreamer Pipeline.
Web data plays a central role in enterprise data integration, serving as a primary input across pipelines. It can be sourced from partner networks, internal systems, or the open web to support scalable data workflows.
Make your web data work harder. With Datastreamer, you can enrich, filter, join, structure, store, or search data effortlessly using hundreds of out-of-the-box operations.
Web data, unlocked. Datastreamer empowers you to expand your Pipelines as needed while removing friction from your operations.
Add Datastreamer components to your data stack and explore its full capabilities
