What Is a Good Comment-to-View Ratio for YouTube Shorts? We Analyzed 16,063 Videos

Your YouTube Short gets 10,000 views and five comments.

Is that good?

What if another Short reaches one million views but receives only 150 comments?

Does a low comment count mean viewers aren't interested? And do Shorts with more comments actually get recommended more often?

These questions matter because creators frequently use comments as a measure of engagement, yet there's surprisingly little reliable, Shorts-specific benchmarking available.

Some guides recommend a 1% comment rate.

Others suggest a fraction of that.

But those numbers can represent radically different levels of performance depending on how they're calculated.

So we investigated.

OverseerOS analyzed 16,063 short-form YouTube videos across 1,142 channels, comparing public comment counts against public views recorded approximately 7–30 days after publication.

The result was considerably lower than many generic engagement benchmarks.

The median Short received 0.518 comments per 1,000 public views.

That's approximately:

• 5 comments per 10,000 views.
• 52 comments per 100,000 views.
• 518 comments per million views.

But the most interesting finding wasn't the overall benchmark.

It was how dramatically comment rates changed as videos reached larger audiences.

Among 202 channels with enough videos in both comparison groups, 151 had higher median comment rates on their 10K–100K-view Shorts than on their Shorts with at least 100K views.

The median high-reach/medium-reach comment-rate ratio was just 0.635x.

In other words, higher-view videos frequently attracted fewer public comments relative to their views.

And video duration revealed another substantial difference.

Shorts lasting 61–180 seconds had roughly three times the pooled median comment rate of Shorts lasting 30 seconds or less.

The takeaway: Approximately 0.5 comments per 1,000 public views was typical in our selected 2026 Shorts dataset. Around 1.4 per 1,000 placed a video near the top quarter, while five per 1,000 was relatively uncommon. But comment rate alone cannot establish whether a video is successful or whether YouTube will recommend it.

Here's what the original research reveals and how creators can use it.

Key Findings: YouTube Shorts Comment Rate Benchmarks

OverseerOS examined public YouTube video observations collected between October 2 and November 1, 2026.

Each qualifying video had at least 500 public views, an available comment count, and one selected observation between days 7 and 30 after publication.

Source: OverseerOS original research, November 1, 2026. Public YouTube video statistics from the production research corpus.

Important: This is an observational study of a selected research corpus, not an official YouTube-wide engagement benchmark. Some recorded zero comment counts may reflect disabled comments or other availability limitations.

The direct answer: What is a good comment-to-view ratio for YouTube Shorts?

Based on our analysis of 16,063 Shorts:

These are descriptive reference points, not official algorithmic thresholds.

A Short can achieve millions of views with a low comment rate.

A Short can also have an unusually high comment rate while reaching relatively few people.

To judge performance properly, consider comment rate alongside views, audience retention, engaged views, subscribers gained, and the channel's normal performance.

How to Calculate Your YouTube Shorts Comment-to-View Ratio

The formula is simple.

Comment-to-view ratio = (Public comments ÷ Public views) × 100

For example, suppose your Short receives:

• 50,000 views.
• 40 comments.

The calculation is:

40 ÷ 50,000 × 100 = 0.08%

That's a comment-to-view ratio of 0.08%.

But because comments are much less common than views, percentages can be awkward to compare.

That's why our study primarily expresses the result as comments per 1,000 views.

Comments per 1,000 views formula

Comments per 1,000 views = (Public comments ÷ Public views) × 1,000

Using the same example:

40 ÷ 50,000 × 1,000 = 0.8 comments per 1,000 views

Both formulas measure the same relationship.

Quick conversion table

These are mathematical conversions, not observed individual-video results.

One particularly important distinction:

Five comments per 1,000 views is a 0.5% comment rate, not a 5% comment rate.

Confusing those units can create misleading engagement benchmarks.

Finding 1: The Typical Short Received About One Comment per 1,900 Views

Let's begin with the overall distribution.

We calculated comments per 1,000 public views for each qualifying video.

Then we examined the percentiles.

Comment-rate distribution

The median of 0.518 comments per 1,000 views is equivalent to approximately one comment per 1,931 recorded views.

That doesn't mean each comment came from a different person, or that a new comment reliably arrives after every 1,931 views.

It simply expresses the observed ratio.

What does this mean for creators?

Imagine your Short receives 100,000 views and 50 comments.

That's:

50 ÷ 100,000 × 1,000 = 0.5 comments per 1,000 views

Your result would be close to the observed median.

Now suppose it receives 150 comments.

150 ÷ 100,000 × 1,000 = 1.5 comments per 1,000 views

That's slightly above the 75th-percentile benchmark.

Why the median matters

Large platforms contain extreme outliers.

Some videos generate enormous discussions.

Others attract millions of views but comparatively few comments.

The arithmetic average can be disproportionately influenced by unusual results.

A median gives creators a more useful description of the middle of the distribution.

However, the median is still specific to the research sample.

It should not be treated as a universal YouTube target.

Finding 2: The Channel-Balanced Median Was Also 0.518 Comments per 1,000 Views

A common problem in large video studies is that prolific channels contribute many more uploads than smaller creators.

One channel might contribute 100 videos.

Another might contribute three.

If we simply pool all the videos, the first channel has much more influence.

To reduce that imbalance, we calculated a separate median comment rate for each channel.

We then compared those channel medians.

For this analysis, channels needed at least five qualifying videos.

That produced:

758 channels.

Channel-balanced results

The result was strikingly consistent.

The video-level median and the channel-balanced median were both approximately 0.518 comments per 1,000 public views.

That suggests the central benchmark wasn't driven entirely by channels contributing unusually large numbers of videos.

How to use this benchmark

Suppose your channel's last twenty Shorts have a median comment rate of 0.3 per 1,000 views.

Your latest Short receives 1.2 per 1,000.

That may represent a meaningful increase relative to your own recent performance.

But whether it's strategically valuable depends on the comments.

Did viewers ask questions?

Did they request more videos on the topic?

Were they expressing appreciation or confusion?

Were the comments primarily spam?

The ratio tells you how much recorded conversation exists relative to public reach.

It does not measure the quality of that conversation.

Finding 3: Comment Rates Were Lower on Million-View Shorts

This was one of the clearest patterns in our study.

We grouped videos by public view count.

Then we calculated each group's median comments per 1,000 views.

Comment rate by video reach

The trend was substantial.

The 1K–9.9K-view group had a median of approximately 0.81 comments per 1,000 views.

The million-view group had a median of only 0.136.

That's roughly one-sixth as many comments per 1,000 views.

Why did the 500–999-view category have a median of zero?

Because more than half of the videos in that category had a recorded zero comment count.

Specifically, 445 of 883 had no recorded comments.

A zero median in this small-view category doesn't mean small videos cannot generate discussion.

It means the central observation in that group was zero.

This also shows why low-volume videos can produce unstable engagement ratios.

One additional comment on a 500-view Short changes its comment rate by two comments per 1,000 views.

The same additional comment on a million-view Short barely changes the rate.

Why might larger videos have lower relative comment rates?

Several explanations are plausible.

A video reaching a broad audience may attract many casual viewers who watch but don't comment.

Repeat playback may increase public views without creating additional comments.

Different topics may generate different levels of conversation.

And some content formats are naturally more discussion-oriented than others.

But these are hypotheses.

Our observational data cannot identify which explanation caused the pattern.

Finding 4: Within 202 Channels, Higher-Reach Shorts Usually Had Lower Comment Rates

A pooled comparison can be misleading because different channels appear in different view groups.

So we repeated the analysis within individual channels.

We compared two categories:

Medium-reach Shorts: 10,000 to fewer than 100,000 public views.

Higher-reach Shorts: At least 100,000 public views.

Each channel needed at least three qualifying videos in both categories.

That produced 202 channels.

Within-channel results

The median high-reach/medium-reach comment-rate ratio was:

0.635x.

In other words, the median channel-level ratio was approximately 36.5% below parity.

Why this is important

The decline wasn't simply a comparison between small and large creators.

Many of the same channels had lower comment rates on their higher-view Shorts.

We also required at least five qualifying videos in both categories.

That produced 136 channels.

Of those:

• 104 favored the medium-reach category.
• 26 favored the higher-reach category.
• The remainder were tied.

The directional pattern persisted.

Does reaching more viewers cause the comment rate to fall?

Not necessarily.

Our research doesn't establish causation.

A video that reaches 500,000 people may have a different topic, audience, or viewing pattern from one that reaches 20,000.

And the public-view denominator can include repeated playback starts.

The supported conclusion is that larger public-view totals frequently coincided with lower relative comment activity, even within the same channels.

That is a useful reason not to judge a viral Short solely by its comment percentage.

Finding 5: Most Million-View Shorts Had Fewer Than 0.5 Comments per 1,000 Views

We examined the 1,545 qualifying Shorts with at least one million public views.

Among them:

1,280 had fewer than 0.5 comments per 1,000 views.

That's approximately 82.8% of the million-view group.

We also found 136 million-view Shorts with a recorded comment count of zero.

Those zero counts require caution because our dataset does not establish whether comments were disabled, unavailable, or genuinely absent.

What this means

A low comment rate does not prevent a Short from accumulating a very large number of public views.

In our sample, it was actually common among million-view videos.

But the finding should not be interpreted as saying comments don't matter.

YouTube's official recommendation-system documentation identifies comments among the forms of engagement that can help inform its understanding of viewers.

Comments are part of a broader set of signals.

They are not a published standalone ranking formula.

Why high public views and low relative comments can coexist

Imagine a Short with:

• 2,000,000 public views.
• 500 comments.

Its comment rate is:

500 ÷ 2,000,000 × 1,000 = 0.25 comments per 1,000 views

That is below our observed median.

But the video has still accumulated two million public views and 500 comments.

It would be misleading to call the video unsuccessful solely because its comment rate is relatively low.

Its retention, engaged views, subscriber gains, and content objectives matter too.

Finding 6: Five Comments per 1,000 Views Was Uncommon

Some creators aim for a 0.5% comment-to-view ratio.

That means five comments per 1,000 views.

How common was it?

In our sample:

896 of 16,063 Shorts reached at least five comments per 1,000 views.

That's approximately 5.6%.

The 95th-percentile value was 5.324 comments per 1,000.

So five comments per 1,000 placed a video toward the upper end of the observed distribution.

Is a 0.5% comment rate good for YouTube Shorts?

Yes, relative to this dataset, it was a comparatively strong result.

But it was not typical.

And it isn't an official threshold that guarantees additional recommendations.

Does a high comment rate guarantee more views?

No.

The group of Shorts with at least five comments per 1,000 views had a median of 4,525 public views.

By comparison, the group with 0.1 to fewer than 0.5 comments per 1,000 had a median of 69,690 public views.

That does not prove comments reduce reach.

It reflects the fact that comment rate and total views measure different things.

A smaller, highly engaged audience can generate an unusually high comment percentage.

A massive audience can create much greater reach without the same relative discussion activity.

High engagement intensity and high absolute reach are not interchangeable.

Finding 7: Longer Shorts Had Higher Comment Rates

We also examined whether comment rates varied with video duration.

We grouped the qualifying videos into three categories.

Comments per 1,000 views by duration

The longest duration category had approximately 3.1 times the pooled median comment rate of the shortest category.

This was a substantial association.

But longer Shorts may cover different subjects, involve more storytelling, or attract different audiences.

So we examined the pattern within channels.

Within-channel duration comparison

We identified channels with at least three qualifying Shorts lasting up to 30 seconds and at least three lasting 61–180 seconds.

That produced 89 channels.

The results:

• 69 channels had higher median comment rates on their longer Shorts.
• 11 channels favored their shorter Shorts.
• Nine channels were tied.

The median longer/shorter comment-rate ratio was approximately:

1.75x.

Should you make your Shorts longer to get more comments?

Not automatically.

The data suggests longer short-form content was associated with greater relative comment activity in many channels.

But it doesn't establish that adding duration causes viewers to comment.

A longer educational explanation may naturally invite questions.

A longer narrative may encourage discussion about the ending.

A brief visual joke may generate many views without encouraging much conversation.

Those are plausible differences, not experimentally established explanations.

Your choice of duration should start with the content.

Use as much time as the idea needs, then assess the overall viewing experience.

For additional evidence, see our YouTube Shorts length study.

Finding 8: Zero Comment Counts Can Distort Shorts Engagement Benchmarks

One of the most important limitations in this research is the distinction between:

A recorded zero comment count

and

A video whose audience had a normal opportunity to comment but chose not to.

Those are not necessarily equivalent.

In our final sample, 2,500 videos had a recorded comment count of zero.

That's approximately 15.6%.

Why can a YouTube video have zero comments?

Several possibilities exist.

• Viewers may not have posted any comments.
• The creator may have disabled comments.
• The video may be designated as made for kids.
• Moderation may affect which comments appear publicly.
• The public data observation may not fully represent comment availability.

According to YouTube's official comment settings documentation, creators can turn comments off, pause comments, or hold comments for review.

YouTube also disables comments on content designated as made for kids.

Our research system did not independently verify every video's comment-permission state.

That means some zeros should be treated cautiously.

We repeated the benchmark without zero-comment records

Excluding all videos with a recorded zero comment count left:

13,563 videos.

Their median comment rate was:

0.713 comments per 1,000 views.

Compare that with the primary result:

The benchmark increased by approximately 38% when zero-count videos were excluded.

That's a meaningful difference.

Which benchmark should you use?

If you're comparing public Shorts without knowing whether comments were enabled, the main 0.518 figure describes our qualifying sample.

If you're comparing videos known to have an active comment section, the positive-count result provides an additional reference, though it excludes genuinely zero-comment videos too.

Neither measure is a universally correct benchmark for every channel.

The main lesson is to define your comparison population.

A reliable engagement benchmark should explain how it handles videos that cannot receive comments.

Does a High Comment Rate Help the YouTube Shorts Algorithm?

Comments can provide information about audience response.

But YouTube does not publish a universal comment-rate threshold required for a Short to receive recommendations.

In its Shorts search and discovery guidance, YouTube identifies several performance and personalization signals.

These include:

• Whether viewers choose to watch.
• Whether they continue watching.
• Average view duration.
• Average percentage viewed.
• Likes and satisfaction responses.
• Audience interests.
• Topic demand.
• Competition.

YouTube's broader recommendation-system explanation also discusses comments among forms of engagement it considers.

But neither source establishes that a particular number of comments per 1,000 views guarantees more recommendations.

Why comments aren't the whole picture

A Short may generate many comments because viewers:

• Enjoyed the video.
• Learned something new.
• Want to ask a question.
• Disagree with the creator.
• Found a mistake.
• Want additional context.
• Are responding to one another.

Those reactions are not equivalent.

A comment count doesn't reveal sentiment or satisfaction by itself.

That's why a high comment rate can be useful without necessarily being a sign of positive audience response.

Can controversial Shorts get high comment rates?

Potentially.

A divisive topic may encourage viewers to argue.

But our research did not classify comment sentiment or experimentally compare controversial content with neutral content.

We cannot conclude that deliberately creating controversy improves distribution.

For a sustainable content strategy, meaningful viewer interest is more valuable than simply manufacturing arguments.

Why Public Views Make Comment Rates Look Smaller

Another factor matters when interpreting the denominator.

Since March 31, 2025, YouTube has counted a Shorts public view when a Short starts to play or replay, without requiring a minimum watch time.

YouTube extended this first-frame view-counting approach across other video formats beginning August 24, 2026.

These updates are documented in YouTube's official Shorts creation guide and its 2026 view-counting announcement.

Public views are not unique viewers

A person may play the same Short more than once.

Each eligible playback can contribute to the public view count.

But that doesn't necessarily create an additional comment.

Therefore, a video can accumulate many public views without a proportionate increase in comments.

Public views vs. engaged views

YouTube maintains an Engaged views metric in YouTube Analytics.

That provides information about viewers who chose to continue watching.

Our study used public views because those were the available comparable observations.

We did not have competitors' private engaged-view counts.

Therefore:

Don't compare our public-view-based comment benchmark directly with a ratio calculated using engaged views.

The denominator is different.

How Our Results Compare With Other 2026 Shorts Research

One reason this topic deserves a dedicated study is that independently published Shorts-specific benchmarks are still relatively limited.

A useful comparison comes from YTDetective's September 2026 YouTube Analytics study.

That study examined public engagement metrics from a sample of tracked YouTube channels.

Its Shorts sample included:

1,707 videos from 78 channels.

It reported:

• Median comments per 1,000 views: 0.34.
• Middle-half range: 0.11–0.74 comments per 1,000 views.

Our sample was larger and produced a higher median.

Comparing the research

The figures are not directly interchangeable.

YTDetective used videos at least fourteen days old with at least 1,000 views.

It also verified its short-form classification using video duration and observed Shorts-page behavior.

Our dataset used a 500-view minimum, selected observations between days 7 and 30, and relied on OverseerOS's recorded short-form classification.

The channel populations and observation periods also differed.

What both studies suggest

Despite the different medians, both studies found comment rates substantially below one comment per 1,000 public views.

That is useful context.

It also shows why generic YouTube engagement advice can be misleading if it mixes comments, likes, and other engagement types into one percentage.

A 0.5% total engagement rate is not the same as a 0.5% comment-to-view ratio.

And public Shorts engagement benchmarks shouldn't be compared with long-form results without accounting for different viewing patterns.

What Is a Good Number of Comments for 10K, 100K, or 1M Shorts Views?

The following table converts our research percentiles into illustrative comment counts.

These are calculations based on the selected benchmark values, not forecasts of what a specific video will receive.

This table is useful for understanding the formula.

However, there's an important caveat.

The median comment rate was not constant across view-count categories.

For million-view Shorts, our observed median was just 0.136 comments per 1,000 views.

That corresponds to approximately 136 comments per million public views.

So a million-view Short with 150 comments would be much closer to its own reach-category median than the overall benchmark suggests.

The better comparison

When evaluating a particular Short, consider:

1. Its comment rate.
2. The normal comment rate of the channel.
3. Comparable videos with similar public views.
4. Similar content types.
5. Whether comments are enabled.
6. The quality and substance of the discussion.

A single generic percentage misses important context.

How to Check Your YouTube Shorts Comment Rate

You can calculate this metric directly from your own channel.

Step 1: Open YouTube Studio

Navigate to:

YouTube Studio → Content → Shorts

Select the Short you want to analyze.

You can also review channel-level performance in YouTube Analytics.

YouTube explains these reports in its Shorts Analytics documentation.

Step 2: Record views and comments

Use numbers measured at the same point in time.

For example:

• Public views: 80,000.
• Comments: 64.

Step 3: Calculate the ratio

64 ÷ 80,000 × 1,000 = 0.8 comments per 1,000 views

That is a comment-to-view ratio of:

0.08%.

Step 4: Compare against your own baseline

Calculate the same metric for several recent Shorts.

If your median is 0.3 comments per 1,000 views, a result of 0.8 represents a substantial increase relative to your normal performance.

But it doesn't establish the cause.

Review the topic and the actual comments.

Step 5: Read what people are saying

Comment count is a quantity metric.

The comment section contains qualitative information.

Look for:

• Repeated questions.
• Requests for follow-up explanations.
• Points of confusion.
• Unanswered viewer needs.
• Corrections.
• Suggestions for related topics.

Those patterns can be more useful for planning your next video than the raw ratio alone.

How to Increase Meaningful Comments on YouTube Shorts

If your objective is to build a community rather than simply maximize a percentage, focus on giving viewers a genuine reason to contribute.

YouTube's official Shorts community-building guidance specifically recommends encouraging feedback and using viewer comments as inspiration for future content.

1. Ask a question that matters to the video

A generic request such as "Comment below!" gives viewers little reason to participate.

A relevant question can be more useful.

For example, after a Short explaining a surprising engineering solution:

"Which engineering problem should I explain next?"

That connects the request to the viewer's interest.

2. Create videos that invite informed discussion

Some subjects naturally generate questions.

An explanation of a complex scientific process may leave viewers curious about a related detail.

A comparison may invite viewers to share an example.

A historical account may inspire questions about the events that followed.

Choose the discussion prompt based on the topic.

3. Respond to valuable questions

If viewers ask thoughtful questions, answer them when practical.

That helps make the comment section useful.

It can also reveal where the original explanation wasn't sufficiently clear.

4. Turn recurring questions into new videos

Suppose a Short about desalination generates repeated questions about what happens to the removed salt.

That is useful evidence of a potential follow-up topic.

Rather than guessing what viewers want next, you can investigate a question they've already expressed.

5. Avoid artificial controversy

A deliberately misleading claim might generate comments.

But that doesn't mean it creates satisfied viewers.

For long-term audience growth, trust matters.

A strong content strategy should encourage real curiosity and useful discussion, not manufacture arguments for engagement.

How OverseerOS Helps You Find Video Ideas From Audience Engagement

The most valuable comments aren't necessarily on the videos with the highest comment ratios.

They're the ones that reveal unmet audience demand.

Step 1: Find unusually successful videos

Use the OverseerOS Viral Outlier Library to investigate videos performing above their channels' normal levels.

Look for topics that attracted unusually strong audience interest.

A video with 20,000 views on a channel that normally receives 500 may be an interesting opportunity, even if its comment count is relatively modest.

Step 2: Analyze the creator's broader performance

Open the OverseerOS YouTube Channel Analyzer.

Review the channel's public uploads, topics, views, and available engagement signals.

Try to distinguish a one-off breakout from a repeatable subject pattern.

A high comment rate isn't enough to validate a niche.

But comments can help you understand what viewers are curious about.

Step 3: Research audience questions

Use public comments to investigate recurring questions and unmet information needs.

Our previous study, How to Analyze YouTube Comments for Video Ideas, explored this approach using 27,555 classified comments.

The key principle is to identify patterns rather than relying on isolated remarks.

A repeated viewer question may be worth investigating.

But one highly emotional comment doesn't necessarily represent broad audience demand.

Step 4: Turn the opportunity into an original script

Use the OverseerOS Content Planner to organize researched topics, reference material, scripts, and production assets.

This connects public channel research with the process of creating original videos.

The objective isn't to copy a competitor.

It's to understand what the audience finds interesting and develop a stronger, original explanation.

Don't chase comments as a vanity metric. Use them as feedback that can make your next video better.

Research Methodology: How We Analyzed 16,063 Shorts

This research was conducted on November 1, 2026, using read-only queries against OverseerOS's production research database.

Dataset

The final sample included:

• 16,063 unique short-form videos.
• 1,142 unique channels.
• Available public comment counts.
• Available public view counts.
• Recorded publication timestamps.
• Video durations.
• Selected observation ages.

The videos were published between September 1 and October 25, 2026.

The selected public observations were collected between October 2 and November 1, 2026.

Eligibility criteria

Each qualifying video needed:

1. A valid video ID.
2. A valid channel ID.
3. A recorded short-form classification.
4. At least 500 public views.
5. An available, nonnegative public comment count.
6. A comment count no greater than the public view count.
7. A qualifying observation between video ages 7 and 30 days.

Observation selection

We retained one public-view and comment-count observation per video.

The selected observation was the one closest to day 21 after publication.

If two observations were equally close, we selected the more recent one.

This prevented videos that were monitored more frequently from contributing multiple measurements.

Comment-rate calculation

For every qualifying video:

Comments per 1,000 views = Comment count ÷ View count × 1,000

We calculated each video's ratio separately.

Then we calculated the median and other percentiles of those video-level ratios.

We did not divide total comments across the entire sample by combined views and describe that as the typical video.

Those are different aggregation methods.

View-count categories

We grouped videos into:

• 500–999 views.
• 1K–9.9K views.
• 10K–99.9K views.
• 100K–999.9K views.
• 1 million or more views.

Duration categories

We grouped videos into:

• 1–30 seconds.
• 31–60 seconds.
• 61–180 seconds.

Channel-balanced analysis

We calculated each channel's median comment rate.

For the main channel-balanced benchmark, channels needed at least five qualifying videos.

That produced 758 channels.

Within-channel reach comparison

We compared:

10K–99.9K-view Shorts versus Shorts with at least 100K views.

Each channel needed at least three qualifying videos in each group.

That produced 202 channels.

We also repeated the comparison with a stricter five-video minimum.

Within-channel duration comparison

We compared:

Shorts lasting up to 30 seconds versus Shorts lasting 61–180 seconds.

Each channel needed at least three qualifying videos in both categories.

That produced 89 channels.

Sensitivity checks

We repeated the main benchmark using alternative inclusion rules.

The median remained close to 0.5 comments per 1,000 views under several alternative filters.

Removing zero-comment videos produced a larger difference.

That is why zero-count handling is especially important when interpreting this metric.

Important Limitations of This Research

1. The sample is not representative of every YouTube Short

OverseerOS's research corpus is a selected collection of publicly observed videos.

It may overrepresent particular channels, niches, and high-performing content.

The results cannot be generalized as the official platform-wide average.

2. We used recorded short-form classification

The videos were classified as short-form by the research system.

We did not independently verify the aspect ratio or Shorts-feed placement of every qualifying upload.

3. Videos below 500 views were excluded

This reduces the instability of very small denominators.

But it also means the research does not represent the entire population of low-reach Shorts.

4. Zero comment counts may not mean no viewer interest

A zero count can arise for reasons other than viewers choosing not to comment.

We could not verify comment-permission status for every video.

5. Comment moderation may influence visible counts

Creators can hold, hide, or remove comments.

The public count may not reflect every attempted interaction.

6. Public comments do not measure unique commenters

One person can post multiple comments.

Comment threads may also include replies.

The ratio does not tell us how many distinct viewers participated.

7. Public views do not measure unique viewers

Since Shorts public views can include starts and replays, the denominator should not be interpreted as the number of distinct people who watched.

8. Video observation ages varied

The primary sample included videos observed between days 7 and 30.

We performed a narrower-age check, but not every video was measured at exactly the same age.

9. Channel contributions were uneven

Some channels contributed more videos than others.

We calculated channel-balanced benchmarks and performed an exclusion check to reduce that concern.

10. Comment-rate differences may reflect different content types

A longer educational Short may prompt questions.

A brief entertainment Short may be watched repeatedly without creating much discussion.

Our data did not independently control for every topic or format difference.

11. We did not measure comment sentiment

Positive, negative, neutral, and spam comments were not reliably classified in this study.

A high comment count does not automatically indicate positive audience response.

12. We did not measure competitors' private analytics

We could not observe every video's engaged views, audience retention, chose-to-view rate, or private traffic-source data.

13. We did not establish causation

The study does not prove that comments cause more views, that more views cause fewer comments, or that longer Shorts cause more discussion.

The findings are observational associations.

14. Public metrics can change

YouTube verifies and may adjust engagement metrics.

Our findings represent selected measurement checkpoints, not final lifetime totals.

15. No single benchmark applies to every niche

Different audiences and formats may produce very different comment behavior.

Your channel's historical median and the actual content of its comments remain important comparison points.

Final Verdict: How Many Comments Should a YouTube Short Get?

Approximately 0.5 public comments per 1,000 public views was typical in our selected October–November 2026 Shorts research sample.

OverseerOS analyzed 16,063 videos across 1,142 channels.

We found:

• A median of 0.518 comments per 1,000 views.
• A 75th-percentile benchmark of 1.432 per 1,000.
• A 90th-percentile benchmark of 3.313 per 1,000.
• A channel-balanced median of 0.518 per 1,000.
• Lower relative comment rates on many higher-view Shorts.
• Higher relative comment rates on many longer Shorts.
• A meaningful difference when zero-comment observations were excluded.

The conclusion isn't that every Short should receive exactly one comment per 2,000 views.

It's that comment activity is usually a relatively small percentage of public Shorts views, and that percentage varies substantially with reach, format, and comment availability.

A video with 100,000 views and 30 comments is not automatically failing.

A video with 10,000 views and 100 comments is not automatically successful.

Comments are one piece of audience evidence.

The more valuable question is:

What are those comments revealing about what your viewers care about?

Use OverseerOS to discover unusually successful videos, analyze relevant channels, and turn audience questions into original content opportunities.

Because better YouTube growth doesn't come from chasing a single engagement ratio.

It comes from understanding the audience behind the numbers.

Frequently Asked Questions

What is a good comment-to-view ratio for YouTube Shorts?

Around 0.5 comments per 1,000 public views was typical in OverseerOS's study of 16,063 Shorts. Approximately 1.4 per 1,000 marked the 75th percentile, while 3.3 per 1,000 marked the 90th percentile.

How many comments should a YouTube Short get with 1,000 views?

At our observed median, approximately 0.5 comments per 1,000 views. Individual Shorts may receive zero, one, or several comments. Small view counts make the ratio more volatile.

How many comments is good for 10,000 Shorts views?

Approximately five comments corresponds to the observed median. Around fourteen corresponds to the 75th-percentile ratio. These are descriptive benchmarks, not guaranteed results.

Is 50 comments on 100,000 YouTube Shorts views good?

That equals 0.5 comments per 1,000 views, close to the overall observed median in our research. Performance should also be compared with similar videos and the channel's normal results.

Is 100 comments on 10,000 views good?

That equals ten comments per 1,000 views, or a 1% comment-to-view ratio. This is well above the observed 95th-percentile benchmark in our sample.

What is a good comment rate for a million-view Short?

Our million-view category had a median of 0.136 comments per 1,000 public views, equivalent to approximately 136 comments per million views. The ratio varied considerably between videos.

Is a 0.1% comment rate good for YouTube Shorts?

A 0.1% comment rate equals one comment per 1,000 views. That was above the overall median of 0.0518% in our dataset.

Is a 0.5% comment rate good?

Yes. A 0.5% comment rate equals five comments per 1,000 views. Only approximately 5.6% of the qualifying Shorts in our sample reached that level.

Do comments help YouTube Shorts get more views?

YouTube considers engagement within its broader recommendation system, but it doesn't publish a fixed comment threshold that guarantees additional distribution. Our study does not establish that increasing comments causes more views.

Can YouTube Shorts go viral with very few comments?

Yes. Our dataset included many million-view Shorts with relatively low comment rates. High absolute reach and high relative comment activity are different outcomes.

Why does my YouTube Short have views but no comments?

Possible explanations include viewers not choosing to comment, comment restrictions, moderation, or unavailable public engagement data. Check your comment settings before concluding that the audience is uninterested.

Does YouTube disable comments on Shorts made for kids?

Yes. YouTube disables comments on videos designated as made for kids, including Shorts.

Are comments more important than likes on YouTube Shorts?

YouTube considers multiple forms of viewer response. It does not publish a universal rule establishing that comments are always more important than likes. Both should be evaluated alongside viewing behavior and satisfaction.

What is the difference between comment rate and engagement rate?

Comment rate measures comments relative to views. Engagement rate may combine multiple interactions such as likes, comments, and shares. Always check the formula before comparing benchmarks.

Why do longer Shorts get more comments per view?

Our research found higher observed comment rates among longer Shorts, including in a within-channel comparison. But the study did not establish why. Different content formats, topics, and viewing behavior may contribute.

Do controversial Shorts get more comments?

Controversial topics may encourage discussion, but this study did not classify sentiment or isolate controversy as a cause. A high comment count does not necessarily indicate positive viewer satisfaction.

Should I ask viewers to comment on every Short?

A relevant question can help invite genuine feedback. Repeating generic requests in every video may be less useful than asking something directly related to the content. YouTube recommends using comments to understand and interact with your audience.

Does replying to comments improve Shorts performance?

Replying can support audience interaction, but our study did not test whether creator replies increase reach. Focus on useful responses and genuine community engagement rather than expecting a guaranteed algorithmic boost.

Can a Short with zero comments still perform well?

Yes. A zero recorded comment count does not establish that a video is unsuccessful. Some videos may also have comments disabled or unavailable, which complicates the comparison.

How can I increase meaningful comments on YouTube Shorts?

Create original videos around relevant audience interests, deliver satisfying explanations, ask specific questions when appropriate, and respond to useful viewer feedback. Measure the quality of discussion as well as the count.

How can I use comments to find new YouTube video ideas?

Look for repeated questions, missing explanations, corrections, and viewer requests. Investigate those patterns and develop original content that addresses the underlying audience need.