Analyze survey response sentiment using AI

Below is a free classifier that uses AI to analyze the sentiment of survey responses. Outputs include neutral, negative, or positive.

survey response sentiment identifier

How this classifier works

This free tool looks at textual survey responses and analyzes them for sentiment. It'll tell you whether the text is positive, negative, or neutral. Request API access to analyze as many text rows as you need.

This pretrained text model uses the tweet_eval dataset and is built with 24993 samples across 3 labels, including Negative, Neutral, & Positive.

We'll also show a confidence score (the higher the number, the more confident the AI model is of which emotion it is).

Whether you’re a tech-minded product manager, just curious, or building survey response sentiment detection into your application, we hope our classifier proves helpful.

Need to identify survey response sentiment at scale?

Get API or Zapier access to this classifier for free. It's perfect for:

  • Market Research: Sort open-ended survey responses into thematic categories to streamline qualitative analysis.

  • Event Management: Categorize participant feedback from events to tailor future planning and improve attendee satisfaction.

  • Human Resources: Aggregate employee feedback from surveys to address workplace environment issues.

  • Product Development: Use survey data to identify customer preferences and guide new product features.

  • Healthcare: Classify patient survey responses to identify common concerns and improve service delivery.

  • Customer Service: Automatically organize customer satisfaction survey results to quickly address service gaps

  • Education: Analyze student feedback on courses and instructors to enhance educational offerings.

Want this classifier for your business?

In just minutes you can automate a manual process or validate your proof-of-concept.

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