Sentiment & Emotion Classifier

What the sentiment & emotion classifier does

Paste any text and get a breakdown across seven emotions — joy, sadness, anger, fear, surprise, disgust, and neutral — rather than a flat positive/negative label. It's powered by a Hugging Face emotion model, so your text is sent to the model to classify. No signup.

How to classify text

1. Paste a sentence, review, message, or paragraph.
2. Read the emotion breakdown with a score per emotion.
3. Use the dominant emotion, or the full distribution, in your analysis.

Emotion vs plain sentiment

Classic sentiment analysis collapses everything to positive, negative, or neutral — useful, but blunt. A message can be "negative" out of anger or out of fear, and those call for very different responses. A multi-emotion model keeps that nuance, which matters for support triage, moderation, and understanding user feedback.

Chain it with other models: transcribe audio first with Whisper, then classify the transcript's tone here — or explore image understanding with Vision Q&A.