Overview
YouTube Sentiment Detector collects comments from a video or channel, computes positive/negative/neutral ratios, and helps you quickly grasp overall sentiment. It uses an AI sentiment classification model; results are intended as reference signals.
Getting Started: Video Analysis
On the main page, enter a video URL (e.g. https://www.youtube.com/watch?v=VIDEO_ID) and click Search. You will be taken to the analysis page. Click "Collect Comments" to gather comments, then "Analyze Sentiment" to run the analysis. Up to 300 comments are collected in relevance order.
Channel-Level Analysis
Enter a channel URL (e.g. https://www.youtube.com/@channel_name) to see the channel's recent videos. Select a video to open its analysis page and follow the same steps to collect and analyze comments.
Using the Trending List
The "Trending Videos Now" section at the top shows videos currently trending in your selected region. Click "Analyze Sentiment" on any card to go directly to its analysis page. Change the region to see trending content from other countries.
Reading the Results
After analysis, positive/negative/neutral ratio cards appear at the top. High ratios do not mean absolute public opinion. Results vary with comment count, topic, timing, and audience. Interpret alongside the original comments. Click a ratio card to filter comments by that sentiment.
Report Download
You can download a PDF report for analyzed videos. The report includes video info, sentiment summary, and comment list. Use it for meetings or internal review.
Practical Use Cases
Compare reactions before and after thumbnail/title changes, track sentiment shifts from upload to next day, compare reactions across series videos, or check public sentiment on controversial or viral content. Use the comment filter to view only negative or positive feedback.
Limitations
The model may not perfectly handle sarcasm, memes, or mixed-language expressions. Comment count depends on API status, video visibility, and comment settings. A daily usage limit (10 requests) applies. Always review original comments and channel context for final decisions.
FAQ
Q. How accurate is the analysis? A. It is a machine-learning-based estimate for reference; we do not guarantee 100% accuracy. Q. Why are fewer comments shown? A. Collection depends on API status, video visibility, and comment settings. Q. What is this best for? A. Content reaction monitoring, before/after thumbnail/title comparisons, and community issue checks.