AI Sentiment Analysis
Feed in reviews, surveys or social text and AI labels sentiment and emotion with reasons, batch analysis and brand monitoring — MonkeyLearn, Brandwatch and Lexalytics class
Interactive tool will be available soon
Meanwhile, read the guide below to understand how it works
Features
- ✓ Labels each text as positive, negative or neutral with a confidence score
- ✓ Breaks sentiment down into emotions such as joy, anger, disappointment and anticipation
- ✓ Batch-uploads reviews, surveys and social data to chart sentiment distribution
- ✓ Extracts keywords and topics to pinpoint what drives each opinion
- ✓ Supports Chinese, English and other languages with charts and shareable reports
How to Use
- Paste text or upload reviews, surveys and social data files
- Choose the sentiment dimensions and language
- AI analyzes each item and aggregates sentiment and emotion
- Export charts or reports and track how opinion shifts over time
FAQ
What is AI Sentiment Analysis?
An online AI text-sentiment tool. It labels polarity, classifies emotions, extracts topics and supports batch brand monitoring. Input: review text, surveys or social data. Output: sentiment charts, keywords and per-item results. Built for brand, marketing and support teams.
Does it handle Chinese text well?
Leading tools such as MonkeyLearn and Brandwatch support Chinese, English and other languages; Chinese sentiment detection is mature, though slang and sarcasm still need human review.
How many items can it process at once?
Free tiers usually cap items per run or per month; paid plans batch tens of thousands of items and stream real-time data via API.
Can it monitor live social mentions?
Most products ingest social and news sources for continuous monitoring and alert on negative spikes; availability depends on the plan.
How reliable are the results?
AI labels are generally reliable and ship with confidence scores and reasons; spot-check key findings to avoid errors from sarcasm or context.
How much does it cost?
Some tools offer free tiers or trials; batch analysis and live monitoring are typically subscription-based, priced by data volume and seats.