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IntermediateContent

How to Analyze YouTube Comments for Audience Insights with AI

Quickly analyze thousands of YouTube comments for sentiment and new content ideas using the Jev AI model. This workflow helps creators turn audience feedback into actionable insights for their content strategy.

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How to Analyze YouTube Comments for Audience Insights with AI
Source episodeMy Jev Playbook for Data Analysis, Product Insights, and Real-Time Apps

with Claire Vo

Read the full episodeWatch on YouTube

Before you start

Tools used

  • Jev

    TypeSafe AI’s model for fast structured decisions, including choices, scores, and boolean probabilities.

    VisitJev

The workflow

Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.

4 steps

Step 01

Pull YouTube Comments

Use the YouTube v3 API to fetch all the comments from your channel or a specific video.

Step 02

Categorize Comment Sentiment

Feed each comment's text into Jev to classify its sentiment. This is a 'Choice' task where you provide the potential options for Jev to pick from.

Example prompt
Given the following text, categorize the sentiment. Choices: [positive, negative, neutral]
Step 03

Identify New Ideas

Run another Jev classification on each comment to determine if it contains an idea for a future episode. This is a 'Choice' task with a simple yes/no answer.

Example prompt
Does this comment include an idea for a future episode? Choices: [yes, no]
Step 04

Build a Dashboard

Feed the structured data (comment text, sentiment, idea flag) into a dashboarding tool. This allows you to visualize the sentiment breakdown and create a filterable 'request board' of audience ideas.

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