Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Detect insults (profane or not), hate speech, suicidal ideation, attempts to establish external contact, allegations, and more. Counter algospeak and slang.
Automatic detection of problematic content in text, including attempts to lure users off the platform and establish content, profanities, mental issues and suicidal ideation, and more.
Built from scratch for social media content, Tisane handles misspellings, algospeak, bad grammar, jargon. It operates with social content is a manner that is more granular than any other NLP platform.
Tisane problematic content detection supports 35+ languages, including slang and obfuscated text (adversarial text manipulation).
Collect and extract YouTube video and profile search results using keywords, and YouTube comments using URLs. Further refine the video and profile searches by start date and end date using additional parameters.
How Datastreamer works
Quickly apply Tisane Problematic Content Detection to Bright Data YouTube with a Datstreamer Pipeline.
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.
Boost your web data capabilities by applying a wide range of operations—enrich, augment, join, structure, filter, store, search, and more. With Datastreamer, you get access to hundreds of plug-and-play tools to power your workflows.
Datastreamer makes working with web data simpler than ever. Easily enhance your Pipelines with new features and finally eliminate the operational roadblocks that once held you back.
Add Datastreamer components to your data stack and explore its full capabilities
