Skip to main content
Thirdwatchthirdwatch
Social media

Compare Posts And Profiles Across YouTube Comments Scraper at Scale

Compare posts and profiles from YouTube Comments Scraper — a practical guide with a ready-to-run configuration and structured output.

Sep 16, 2026 · 2 min read · 459 words
See the scraper →

Comparisons need the same fields across every row — that's what structured extraction buys you. Thirdwatch's YouTube Comments Scraper turns YouTube Comments Scraper into structured posts and profiles — the fields you need, ready to export.

Skip the setup: Run this as a ready-to-go task on Apify — pre-loaded with the configuration from this guide.

Why compare posts and profiles

'Which is better/cheaper/higher-rated' is a table question. Manual browsing gives anecdotes; a structured pull gives you the sortable, filterable census.

Run the Actor over your full target list and the comparison is a group-by away.

The scraper handles the extraction details so a short input list in means usable posts and profiles out.

How does this compare to the alternatives?

Approach Cost model Coverage Effort
Manual browsing and copy-paste Free Whatever you can read Doesn't scale
Custom one-off script Your infra and maintenance One brittle path You own the upkeep
Thirdwatch YouTube Comments Scraper Pay per result row Structured posts and profiles at scale One run

Why this Actor

  • Purpose-built for this source — videoUrls in, structured rows out.
  • Pay per result — no subscriptions, free tier to test.
  • Dataset output exports as JSON, CSV, Excel, or via API.
  • Schedulable — save the task and run it daily or weekly.
  • Part of the Thirdwatch portfolio — 140+ public Actors maintained as a fleet.

How to do it in 3 steps

Step 1: Configure the input

Set the inputs as shown below — videoUrls takes the targets, the optional fields bound run size — start small and scale.

Step 2: Run the Actor

Run it from the console, the API, or the linked saved task. One dataset row is written per posts and profile.

Step 3: Use the output

Each row carries the fields this source exposes (title, url, description).

{
  "videoUrls": [
    "https://example.com"
  ]
}

Each dataset row looks like:

{
  "title": "\u2026",
  "url": "\u2026",
  "description": "\u2026"
}

What to watch for

Results reflect what's publicly visible at run time. Very large pulls take proportionally longer; bound them with the max/limit fields. For audience research and monitoring, scheduled small runs beat occasional giant ones.

Related use cases

Run the YouTube Comments Scraper on Apify Store — pay per result, free to try, no credit card to test.

Frequently asked questions

What does YouTube Comments Scraper return?

One dataset row per posts and profile — with the fields shown in the sample output. Export as JSON, CSV, or Excel.

How do I control run size?

`videoUrls` selects the targets and the max/limit fields bound how many rows come back. Start small, then scale.

Can I run this on a schedule?

Yes — save it as a task and attach a schedule in Apify Console for daily/weekly pulls.

Is this data public?

The Actor collects publicly visible data only — the same information a logged-out visitor sees.

What formats can I export?

JSON, CSV, Excel, XML, or direct API access to the dataset — plus webhooks and integrations.

What if a run returns fewer rows than expected?

The source limits some results; retry once, and widen the query or filters if the target surface is genuinely thin.

Related

Try it yourself

100 free credits, no credit card.

About 30 real searches. Add the MCP to Claude or Cursor in two minutes.