AI Sentiment Analyzer
Analyze the sentiment of any text — reviews, feedback, emails, comments — using AI that runs 100% in your browser. Detect positive, negative, or neutral tone with confidence scores. Private and free. Works in all browsers.
How AI Sentiment Analysis Works in Your Browser
This tool uses DistilBERT, a lightweight version of Google's BERT language model, fine-tuned for sentiment classification. It runs entirely in your browser through Transformers.js — no server, no API, no data transmission. Your text stays on your device.
The model analyzes the words, phrases, and context of your text to determine whether the overall sentiment is positive or negative, along with a confidence score from 0% to 100%. For batch analysis, each line is analyzed independently, and an overall summary is provided.
How It Works
- Text encoding: Your text is tokenized and encoded into numerical representations that the model can process.
- Neural network inference: DistilBERT processes the encoded text through 6 transformer layers to understand context and meaning.
- Classification: The final layer produces a probability distribution over POSITIVE and NEGATIVE labels.
- Confidence score: The higher probability becomes the sentiment label, and the probability value becomes the confidence score.
Use Cases for Sentiment Analysis
Customer Review Analysis
Paste customer reviews from your product pages, app store, or support tickets. Quickly identify which reviews are positive praise and which are negative complaints. Useful for prioritizing issues and understanding customer satisfaction.
Social Media Monitoring
Analyze tweets, comments, and posts about your brand or topic. Batch-analyze multiple texts to get an overall picture of public sentiment. All analysis happens privately on your device.
Email and Communication Tone Check
Before sending an important email, paste it here to check the tone. The AI will tell you whether your message reads as positive or negative, helping you adjust the wording for the right impression.
Academic Research
Researchers studying opinion mining, political sentiment, or public discourse can analyze text samples without sending them to third-party APIs. Ideal for studies involving sensitive or ethically restricted data.
Content Moderation
Screen user-generated content for negative sentiment. While not a replacement for comprehensive moderation, sentiment analysis provides a useful first-pass filter for identifying potentially problematic content.
Batch Analysis for Multiple Texts
Enter multiple texts, one per line, to analyze them all at once. The tool processes each line independently and shows individual results plus an overall summary with counts of positive and negative results and average confidence. This is ideal for analyzing a list of reviews, survey responses, or social media comments.