Sentiment Analysis

InicialdataContexto mínimo: 16K

Classifies the sentiment and emotional tone of text — reviews, support tickets, social posts, and survey responses. Supports document-level and aspect-based sentiment, returns confidence scores and representative quotes, and aggregates trends across large batches with themes and actionable insights.

sentimentnlptext-classificationreviewsfeedbackanalytics

Casos de uso

  • Classifying customer reviews as positive, negative, or neutral
  • Aspect-based sentiment on product features
  • Triaging support tickets by frustration level
  • Tracking sentiment trends across a batch of survey responses
  • Surfacing representative quotes for each sentiment theme

Prompt de ejemplo

Analyze the sentiment of the following customer reviews. For each review return:
- overall sentiment (positive/negative/neutral) with a confidence score
- aspect-based sentiment (e.g., price, quality, support)
Then provide an aggregate summary: sentiment distribution, top themes, and 3 representative quotes.

Reviews:
```
[paste reviews here]
```

Modelos recomendados

claude-opus-4-8gpt-5-5gemini-3-flashdeepseek-v4

Herramientas compatibles

claude-codekiroany

Modalidades

Entrada: text
→
Salida: text

Skills relacionadas

data-analysisresearch-summarizer

Autor

OpenModels Community

@openmodelsrun