Analyze text sentiment
using AI
Below is a free classifier that uses AI to analyze the sentiment of text. Outputs include positive, negative, and neutral.
How this classifier works
This free tool looks at any text input and analyzes it 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 moderator, just curious, or building text sentiment detection into your application, we hope our classifier proves helpful.
Need to identify text sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Support: Automatically categorize customer feedback from support tickets to prioritize urgent issues.
- Marketing Teams: Analyze social media comments to gauge public sentiment about new product launches.
- Media and Entertainment: Track audience reactions to content across platforms to adjust marketing strategies.
- Healthcare: Assess patient feedback on services for quality control and improvement measures.
- Finance: Screen investor communications for sentiment to better understand market trends
- Customer Service Departments: Improve customer engagement by responding to tweets with negative sentiments more proactively.
- eCommerce: Classify user reviews to identify product strengths and weaknesses.