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Collect and extract comments, video metadata and user profiles on Poal.
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).
How Datastreamer works
Quickly enrich Open Measures Poal with Tisane Problematic Content Detection with a Datstreamer Pipeline.
Web data is the foundation of any pipeline. You can leverage a wide range of data sources to power your pipelines—whether it's data from our partner network, your internal systems, or any publicly available web data.
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
