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Enrich Socialgist News with Datastreamer User Sentiment Classifier
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About Socialgist News
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.
About Datastreamer User Sentiment Classifier
Detect the user sentiment and cause of sentiment within content. 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.
Quickly enrich Socialgist News with Datastreamer User Sentiment Classifier with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Socialgist News
Enterprise-grade data pipelines begin with flexible data ingestion. Web data—sourced from partners, internal platforms, or the open internet—provides the raw inputs needed for integration and transformation.
Step 2
Add Datastreamer User Sentiment Classifier to enrich
Datastreamer lets you accelerate your data usage by applying operations like structuring, enriching, joining, and filtering—choose from hundreds of prebuilt, plug-and-play options.
Step 3
That's it! You have just connected Socialgist News and Datastreamer User Sentiment Classifier
Supercharge your data workflows with Datastreamer. Add flexibility to your Pipelines and put an end to the common bottlenecks in handling web data.