sarih

Arabic sentiment analysis across five dialects (Egyptian, Gulf, Levantine, Maghrebi, Iraqi) detects positive, negative, and neutral sentiment. Provide an Arabic text sample to receive sentiment labels for social listening or dataset labeling.

Yes, you can filter toxic Arabic content offline. The tool runs offline to flag or filter offensive user-generated text, providing toxicity scores to support safer content moderation pipelines without external API dependencies.

The best way to label Arabic corpora is by processing text samples to output sentiment labels alongside toxicity scores. This enables accurate dataset labeling for Arabic-language platforms across five distinct regional dialects.

Yes, the Arabic content filter supports Gulf and Maghrebi dialects, alongside Egyptian, Levantine, and Iraqi. It applies multiple dialect tags to accurately detect sentiment and filter harmful content specific to each regional variation.

No external dependencies are required to run Arabic toxicity detection. The solution operates entirely offline, allowing you to process text, apply dialect tags, and output toxicity scores without connecting to external services.