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Quickly apply Datastreamer Emotion Detection Classifier to Open Measures Odnoklassniki with a Datstreamer Pipeline.
Quickly connect Datastreamer Emotion Detection Classifier and Open Measures Odnoklassniki with a Datstreamer Pipeline.
Web data is the starting point for any pipeline. You can use any number of data sources to power your Pipelines. You can use web data from our partner network, your own systems, or any web data.
To accelerate using your web data, you can apply any number of operations to the data. Enrich, augment, join, structure, filter, storage, search, or more! Datastreamer has hundreds of plug-and-play operations that you can apply.
With Datastreamer it’s never been easier to use web data. You can dynamically expand your Pipelines with more capabilities, and you’ve now been able to solve your operational bottlenecks in working with web data.
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.
Open Measures collection on OK(Odnoklassniki) began by aggregating around 5,000 OK group URLs that appeared across the existing collections and fed these into the crawler. The crawler then spiders across these groups by collecting posts, comments and group members.
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