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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.
Aggregated content from over 2,000 Chinese blogs and over 200,000 diverse English blogs, capturing the pulse of conversations. From niche interest to mainstream topics, Socialgist dataset provides a window into the vast array of perspectives, trend and insights that blog uniquely offer. Harness this rich resource for nuanced understanding of public sentiment, emerging trends, and influential bloggers in various domains.
How Datastreamer works
Quickly apply Datastreamer Emotion Detection Classifier to Socialgist Blogs with a Datstreamer Pipeline.
In modern enterprise architecture, web data fuels integration pipelines by bridging internal systems with external data sources such as partner networks and publicly accessible web content.
Datastreamer puts data control in your hands. Apply hundreds of operations—filter, enrich, structure, join, and beyond—to unlock the full value of your web data.
Empower your data team with Datastreamer. Expand your web data Pipelines effortlessly and clear the operational hurdles that once limited your efficiency.
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