YouTube Comment Insights avatar

YouTube Comment Insights

Pricing

from $80.00 / 1,000 video comments analyzeds

Go to Apify Store
YouTube Comment Insights

YouTube Comment Insights

Analyze YouTube video comments into per-video audience insights. Sentiment breakdown, top keywords, requested topics, questions, and complaints.

Pricing

from $80.00 / 1,000 video comments analyzeds

Rating

0.0

(0)

Developer

Andrew

Andrew

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

a day ago

Last modified

Share

Turn any YouTube video's comments into a single, ready-to-read audience report — sentiment breakdown, most-requested topics, top questions, recurring complaints, and the comments that resonated most. You get the insight layer, not a raw comment dump.

What you get

For every video you submit, one summary record containing:

  • Sentiment breakdown — positive, negative, and neutral percentages plus a single sentiment score, computed with a transparent positive/negative word lexicon
  • Top keywords — the 15 most frequently discussed content words across the comments, each with a count
  • Most-requested topics — comments where viewers ask the creator to do, make, or cover something, with examples and a total request count
  • Top questions — the highest-liked questions your audience is asking
  • Recurring complaints — comments flagged for common gripes (clickbait, too long, boring, audio issues, and more) with examples and a count
  • Most-liked comments — the top 10 comments by like count, with author and likes
  • Video context — title, channel, view count, reported comment count, and how many comments were analyzed
  • Export to JSON, CSV, or Google Sheets directly from the Apify console

Use cases

  • Content planning — see exactly which topics your audience is asking for next
  • Audience research — measure how viewers feel about a video at a glance
  • Competitor analysis — analyze a rival channel's videos to find unmet audience demand
  • Community management — surface the most-liked questions and complaints worth a reply
  • Creator vetting — gauge real audience reception before a sponsorship or collaboration

How it works

Comments are scored with deterministic keyword and sentiment heuristics — a hand-built lexicon of positive and negative words plus pattern matching for requests, questions, and complaints. Results are fully reproducible: the same comments always produce the same report.

How to use

  1. Paste one or more YouTube video URLs or 11-character video IDs into Video URLs or IDs (watch links, youtu.be links, and Shorts links all work)
  2. Set Max Comments Per Video (default 200; up to 1000) — more comments means richer insights
  3. Choose Comment OrderRelevance for top/most-engaged comments, or Newest for the latest
  4. Run the actor — one insight record per video appears in the Dataset tab

If a video has comments turned off, its row is returned with a comments_disabled status so the rest of your batch still completes.

Output format

One dataset record per video:

{
"videoId": "0e3GPea1Tyg",
"videoUrl": "https://www.youtube.com/watch?v=0e3GPea1Tyg",
"videoTitle": "Example video title",
"channelTitle": "Example Channel",
"viewCount": 12000000,
"commentCountReported": 48000,
"commentsAnalyzed": 200,
"totalCommentLikes": 35210,
"sentimentPositivePct": 61.5,
"sentimentNegativePct": 12.0,
"sentimentNeutralPct": 26.5,
"sentimentScore": 0.5,
"topKeywords": [{ "keyword": "editing", "count": 18 }],
"topRequests": {
"count": 14,
"examples": [{ "text": "Please do a video on...", "author": "viewer", "likeCount": 320 }]
},
"topQuestions": [{ "text": "How did you make this?", "author": "viewer", "likeCount": 88 }],
"complaints": {
"count": 6,
"examples": [{ "text": "This was too long", "author": "viewer", "likeCount": 12 }]
},
"mostLikedComments": [{ "text": "Best video yet!", "author": "viewer", "likeCount": 1500 }],
"status": "success",
"error": null
}

Part of a complete YouTube toolkit — explore the rest of the suite: