Key YouTube Statistics (Editor’s Choice) YouTube recorded 70 billion monthly active users in March 2023, which includes 55.10% of worldwide active social media users. There have been more than 14 million daily active users currently on YouTube, in the United States of America this platform is accessed by 62% of users. YouTube is touted as the second largest search engine and the second most visited website after Google. Revenue earned by YouTube in the first two quarters of 2023 is around $14.358 billion. In 2023, YouTube Premium and YouTube Music have recorded 80 million subscribers collectively worldwide. YouTube consumers view more than a billion hours of video per day. YouTube has more than 38 million active channels. In the fourth quarter of 2021, YouTube ad revenue has been $8.6 billion. Around 3 million paid subscribers to access YouTube TV. YouTube Premium has around 1 billion paid users. In 2023, YouTube was banned in countries such as China excluding Macau and Hong Kong, Eritrea, Iran, North Korea, Turkmenistan, and South Sudan. With 166 million downloads, the YouTube app has become the second most downloaded entertainment application across the world after Netflix. With 91 million downloads, YouTube Kids has become the sixth most downloaded entertainment app in the world. Nearly 90% of digital consumers access YouTube in the US, making it the most popular social network for watching video content. Over 70% of YouTube viewership takes place on its mobile application. More than 70% of YouTube video content watched by people is suggested by its algorithm. The average duration of a video on YouTube is 12 minutes. An average YouTube user spends 20 minutes and 23 seconds on the platform daily. Around 28% of YouTube videos that are published by popular channels are in the English language. 77% of YouTube users watch comedy content on the platform. With 247 million subscribers, T-Series has become the most subscribed channel on YouTube. Around 50 million users log on to YouTube every day. YouTube's biggest concurrent views record has been at 2.3 billion from when SpaceX has gone live on the platform to unveil Falcon Heavy Rocket. The majority of YouTube users are in the age group of 15 to 35 years in the US. The male-female ratio of YouTube users is 11:9. Apple INC. has been touted as the biggest advertiser on YouTube in 2020 spending $237.15 million. YouTube produced total revenue of $19.7 billion in 2020. As of 2021, the majority of YouTube users (467 million) are from India. It is the most popular platform in the United States with 74 percent of adult users. YouTube contributes to nearly 25% of mobile traffic worldwide. Daily live streaming on YouTube has increased by 45% in total in 2020. In India, around 225 million people are active on the platform each hour as per the 2021 statistics. YouTube Usage and Viewership Statistics #1. YouTube accounts for more than 2 billion monthly active users Around 2.7 billion users log on to YouTube each month. The number of monthly active users of YouTube is expected to grow even further. #2. Around 14.3 billion people visit the platform every month The number of YouTube visitors is far higher compared to Facebook, Amazon, and Instagram. #3. YouTube is accessible across 100 countries in 80 languages. The platform is widely available across different communities and nations. #4. 53.9% of YouTube users are men and 46.1% of women use the platform As of 2023 statistics, 53.9% of men use the platform and 46.1% of women over 18 years are on YouTube. The share in the number of males and females is 1.38 billion and 1.18 billion respectively. Age Group Male Female 18 to 24 8.5% 6% 25 to 34 11.6% 8.6% 35 to 44 9% 7.5% 45 to 54 6.2% 5.7% 55 to 64 4.4% 4.5% Above 65 4.3% 5.4% #5. 99% of YouTube users are active on other social media networks as well. Fewer than 1% of YouTube users are solely dependent on the platform. #6. Users spend around 20 minutes and 23 seconds per day on YouTube on average It is quite a generous amount of time spent on any social network platform. #7. YouTube is the second most visited site worldwide With more than 14 billion visits per month, YouTube has become the second most visited site in the world. However, its parent company Google is the most visited site across the globe. As per the statistics, YouTube is the third most popular searched word on Google. #8. 694000 hours of video content are streamed on YouTube per minute YouTube has outweighed Netflix as well in terms of streaming video content. #9. Over 81% of total internet users have accessed YouTube #10. Nearly 450 million hours of video content are uploaded on YouTube each hour More than 5 billion videos are watched on YouTube per day. #11. India has the maximum numb

As of January 2025, the music video for Korean boy band BTS single "Butter" -which was released in May 2021- was still the fastest video to reach 100 million YouTube views, achieving the result within less than one day. Up until then, the record first the fastest video to reach 100 million views was held by their video "Dynamite" generating 100 million views within one day from release. The music video for "Pink Venom," released in August 2022 and performed by the Korean girl band Blackpink, reached 100 million YouTube views in 1.4 days. Due to an engaged global fanbase, K-pop acts account for half of the music videos on the fastest viral video ranking. YouTube YouTube is a video sharing website originally founded in 2005. The website was purchased by Google in 2006 for roughly 1.65 billion U.S. dollars in stocks. Since the acquisition, YouTube has grown significantly, becoming the primary source for videos online, such as music videos, tutorials, news, gaming videos and vlogs. During the third quarter of 2024, the popular video platform generated almost nine billion U.S. dollars in advertising revenues alone. Going viral Music videos frequently rank among the most popular new videos on YouTube - the majority of the fastest viral videos based on the number of views in the first 24 hours after upload are music videos. BTS are also featured in the ranking, along with fellow Korean performers Blackpink, PSY, and Twice. The most viewed YouTube video of all times is currently Korean "Baby Shark Dance" with over 9.2 billion views globally.

As of October 2025, male users aged 25 to 34 years accounted for 11.5 percent of YouTube’s global audience, while female users in the same age group represented around 9.8 percent. This made the 25-to-34 age bracket the platform’s largest audience segment worldwide. YouTube’s global popularity The number of monthly active users on YouTube reached almost 2.5 billion in April 2024, making it the second most popular social network on the internet. The platform's popularity spans all over the world, with India and the United States having the largest YouTube audiences. As of April 2024, the audience of YouTube in India was around 476 million, while the United States recorded a YouTube audience of around 238 million users.

YouTube’s digital revenues One of YouTube's leading monetization methods include advertising, with the company generating around 8.09 billion U.S. dollars in the first quarter of 2024. Additionally, the platform generated over 28 million dollars in the United States through in-app purchases, as well as over 19.2 million U.S. dollars in revenues from mobile app users in Japan.

On June 17, 2016, Korean education brand Pinkfong released their video "Baby Shark Dance", and the rest is history. In January 2021, Baby Shark Dance became the first YouTube video to surpass 10 billion views, after snatching the crown of most-viewed YouTube video of all time from the former record holder "Despacito" one year before. "Baby Shark Dance" currently has over 15 billion lifetime views on YouTube. Music videos on YouTube “Baby Shark Dance” might be the current record-holder in terms of total views, but Korean artist Psy’s “Gangnam Style” video remained on the top spot for longest (1,689 days or 4.6 years) before ceding its spot to its successor. With figures like these, it comes as little surprise that the majority of the most popular videos on YouTube are music videos. Since 2010, all but one the most-viewed videos on YouTube have been music videos, signifying the platform’s shift in focus from funny, viral videos to professionally produced content. As of 2022, about 40 percent of the U.S. digital music audience uses YouTube Music. Popular video content on YouTube Music fans are also highly engaged audiences and it is not uncommon for music videos to garner significant amounts of traffic within the first 24 hours of release. Other popular types of videos that generate lots of views after their first release are movie trailers, especially superhero movies related to the MCU (Marvel Cinematic Universe). The first official trailer for the upcoming film “Avengers: Endgame” generated 289 million views within the first 24 hours of release, while the movie trailer for Spider-Man: No Way Home generated over 355 views on the first day from release, making it the most viral movie trailer.

YouTube was launched in 2005. It was founded by three PayPal employees: Chad Hurley, Steve Chen, and Jawed Karim, who ran the company from an office above a small restaurant in San Mateo. The first...

This dataset explores YouTube channel information. It includes:

Channel Names Brand Focus (Gaming, Music, etc.) Subscriber Base (Millions) Primary Languages Content Categories (Broad & Specific) Country of Origin This data allows you to:

Analyze trends by language, category, and region. Identify popular content areas in various locations. Benchmark channel performance. Understand viewer demographics for different content types. By leveraging this dataset, you can gain valuable insights into YouTube's content landscape, audience makeup, and evolving trends.

During the fourth quarter of 2024, YouTube removed around 4.82 million channels from its popular video-sharing platform. This represents a slight decrease from the previous quarter, when the channels removed were approximately 4.87 million. YouTube channels are removed from the platform after three Community Guideline offenses or a single serious offense to the platform's guidelines.

Use our YouTube profiles dataset to extract both business and non-business information from public channels and filter by channel name, views, creation date, or subscribers. Datapoints include URL, handle, banner image, profile image, name, subscribers, description, video count, create date, views, details, and more. You may purchase the entire dataset or a customized subset, depending on your needs. Popular use cases for this dataset include sentiment analysis, brand monitoring, influencer marketing, and more.

The most subscribed YouTube channels in the world are split evenly between brands and individual YouTubers. Many of the most successful company channels actually serve Indian audiences – such as T-Series, SET India, and Zee Music Company. All of these specialize in movies and music, often with Bollywood ties. One name even features twice on our Top 50 list: The main T-Series channel is the second-most subscribed YouTube channel in the world, at over 300 million subs, while its devotional movies channel Bhakti Sagar ranks 27th. Among the 6 non-corporate YouTubers in the Top 10 are the overall leader MrBeast, three kids’ content creators – Kids Diana Show, Like Nastya, and Vlad and Niki – and two newer additions, the Stokes Twins and KIMPRO. They both recently passed by PewDiePie, who has now dropped out of the leaders of the pack. You won’t be surprised that the creator with the most subscribers on the platform is Jimmy Donaldson. After shooting past long-time leader T-Series and first cracking the magic 300 million in mid-2024, then 400 million in June 2025, MrBeast now holds at nearly 450 million. It's an outsize fanbase that earns him an outsize income. We’ve also already mentioned just how popular child YouTubers are. Today, Vlad and Niki hold the #2 creator spot with 146 million subs, now pulling ahead of Kids Diana Show at 137 million (#3). Next come the Stokes Twins, Alan and Alex, who rocketed up this entire list over the last year to become the #4 creators and the #7 top subscribed channel overall. The twin’s antics are now followed by a cool 132 million YouTube subscribers. Like Nastya is not far behind in spot #5, at some 131 million subscribers. The #6 creator channel is the South Korean comedy skit channel 김프로KIMPRO, which features the eponymous Kim Pro and a variable cast of female creators. At 123 million subs, KIMPRO is already the #9 most subscribed channel in the world. It, too, has been growing rapidly, adding millions of fans every month. Next up is former long-term subs leader, video game player PewDiePie AKA Felix Kjellberg (110 million, #7 creator). Kjellberg's channel updates only sporadically, though. It leaked about a million followers over the last year, though it is now rebounding slowly. Rank #8 now belongs to Shorts star Alan Chikin Chow on Alan's Universe. Chow's comedic talent has earned him 97 million followers - nearly 4X what he had two years ago, when he was crowned (once more) the most famous Shorts YouTuber. On the list since the first days of 2025 is Instagram, TikTok and YouTube phenomenon Alejo Igoa, an Argentinian comedian filming silly stuff with his friends. At some 94 million subs, he's already the #9 creator on this list – and he's been climbing fast. Not far behind him comes the comedy skit channel A4, run by a team of Belarusian creators. They've amassed 90 million subscribers. After edging onto the top 50 list at the beginning of last year, A4 are now #20 overall, and the #10 creator channel. Next up is Topper Guild - the TikTok personality whose first dubious claim to fame was wasting food for views, and who has now moved on to glitzy MrBeast-style clips. Having entered the list only in March 2025, he is already the #11 creator with some 79 million fans. Topper is fresh off overtaking Indian family comedy channel KL BRO Biju Rithvik. They made it onto this list just a few months ago, now with 78 million subscribers. This makes them the #12 creator channel. This leaves ex-NASA and Apple engineer Mark Rober in spot #13. His eponymous DIY engineering and science channel now holds 71.5 million subs – and continues to grow steadily, if slowly. A bit over million subs behind him is Uruguayan comedy-horror YouTuber Fede Vigevani. Listed here for a little over a year - since June 2024 - he today has 70 million subscribers, which earns him the #14 creator spot. Additionally, he is the single most-watched Spanish-speaking creator (just ahead of YOLO - see below). The third newbie in 2025 is Japanese Shorts and TikTok creator ISSEI / いっせい, AKA issei0806, whose funny travelogues and parodies of popular content formats launched him onto this list only in June. Issei has already climbed to over 68 million subs and to the #15 creator spot. 2025's fourth new entry are the guys from YOLO AVENTURAS, a Mexico-based pranks, comedy and MrBeast-style challenge channel around Venezuelan Flavio Andrés Broianigo Muñoz (aka YOLO) and his siblings. Their 66 million subscribers make them the #16 creator channel. And: We're fairly optimistic that they'll stay with us. Finally, on #17 with some 65 million subscribers, comes Indian child sensation Anaya Kandhal. Two months ago, she finally shouldered Dude Perfect out of the top 50 YouTubers - despite their big plans. Anaya's channel is also #50 overall, neatly capping off this list.

During the fourth quarter of 2024, around 1.25 billion comments on YouTube videos were removed due to violations of the platform's community guidelines. This represents a slight decrease compared to the previous quarter, when the number of comments removed from the platform were approximately 1.29 billion comments. The majority of removed comments were first detected through automated flagging.

About the Dataset : Youtube Views Prediction

This dataset contains information about trending YouTube videos from multiple countries, providing valuable insights for predicting video popularity based on various attributes. The dataset includes both numerical and categorical features that are essential for analyzing viewer behavior, engagement, and trends in content creation. The original source of this dataset can be found at : https://www.kaggle.com/datasets/datasnaek/youtube-new/data

Columns and Their Descriptions:

title: The title of the YouTube video.
channel_title: Name of the channel that published the video.
trending_date: The date the video started trending.
publish_date: The original upload date of the video.
publish_time: The exact time the video was published.
views: The total number of views the video received.
likes: The number of likes the video received.
dislikes: The number of dislikes the video received.
comment_count: The total number of comments on the video.
tags: Keywords or tags associated with the video, helping discoverability.
description: A detailed text description provided by the uploader.
category_id: The category assigned to the video (e.g., Music, Gaming, News).

Business Goals :

Predicting the number of views on youtube videos based on video attributes. The goal is to develop a model that can accurately predict the number of views a video will receive, using various video attributes such as likes, shares, comments, video duration, and more.

Business Metrics :

1. RMSE (Root Mean Squared Error) RMSE is a metric that measures the magnitude of the error between the values predicted by the model (Predicted Views) and the actual values (Actual Views). The lower the RMSE value, the more accurate the model's predictions.

2. R² (Coefficient of Determination) R² measures the extent to which the model can explain the variation in the data. R² values range from 0 to 1, where 1 means the model can explain all the variation in the number of views based on the given attributes, and 0 means the model cannot explain the variation. The higher the R², the better the model is at predicting views and the more relevant the features used in the model.

Model & Evaluation

The machine learning model was evaluated using several approaches, including different pre-processing techniques and multiple ML models. Ultimately, the chosen model for this analysis is the Random Forest Regressor. The final evaluation results show an RMSE of 630.741, indicating an average prediction error of approximately 630.741 units. Additionally, the R² score is 0.9623, meaning that the model explains 96.23% of the variance in the data (number of views). These results were deemed satisfactory and were selected as the final modeling approach for the system and its potential future applications.

📢 Published on : My LinkedIn

This dataset is a daily record of the top trending YouTube videos and it will be updated daily.

Context

YouTube maintains a list of the top trending videos on the platform. According to Variety magazine, “To determine the year’s top-trending videos, YouTube uses a combination of factors including measuring users interactions (number of views, shares, comments and likes). Note that they’re not the most-viewed videos overall for the calendar year”.

Note that this dataset is a structurally improved version of this dataset.

Content

This dataset includes several months (and counting) of data on daily trending YouTube videos. Data is included for the IN, US, GB, DE, CA, FR, RU, BR, MX, KR, and JP regions (India, USA, Great Britain, Germany, Canada, France, Russia, Brazil, Mexico, South Korea, and, Japan respectively), with up to 200 listed trending videos per day.

Each region’s data is in a separate file. Data includes the video title, channel title, publish time, tags, views, likes and dislikes, description, and comment count.

The data also includes a category_id field, which varies between regions. To retrieve the categories for a specific video, find it in the associated JSON. One such file is included for each of the 11 regions in the dataset.

For more information on specific columns in the dataset refer to the column metadata.

Acknowledgements

This dataset was collected using the YouTube API. This dataset is the updated version of Trending YouTube Video Statistics.

Inspiration

Possible uses for this dataset could include: - Sentiment analysis in a variety of forms - Categorizing YouTube videos based on their comments and statistics. - Training ML algorithms like RNNs to generate their own YouTube comments. - Analyzing what factors affect how popular a YouTube video will be. - Statistical analysis over time.

For further inspiration, see the kernels on this dataset!

Between June 2024 and July 2025, “song” was the most searched keyword on YouTube worldwide, achieving an index value of 100. The term “movie” ranked second, with an index value of 62 points relative to the top search.

rank: Position of the YouTube channel based on the number of subscribers Youtuber: Name of the YouTube channel subscribers: Number of subscribers to the channel video views: Total views across all videos on the channel category: Category or niche of the channel Title: Title of the YouTube channel uploads: Total number of videos uploaded on the channel Country: Country where the YouTube channel originates Abbreviation: Abbreviation of the country channel_type: Type of the YouTube channel (e.g., individual, brand) video_views_rank: Ranking of the channel based on total video views country_rank: Ranking of the channel based on the number of subscribers within its country channel_type_rank: Ranking of the channel based on its type (individual or brand) video_views_for_the_last_30_days: Total video views in the last 30 days lowest_monthly_earnings: Lowest estimated monthly earnings from the channel highest_monthly_earnings: Highest estimated monthly earnings from the channel lowest_yearly_earnings: Lowest estimated yearly earnings from the channel highest_yearly_earnings: Highest estimated yearly earnings from the channel subscribers_for_last_30_days: Number of new subscribers gained in the last 30 days created_year: Year when the YouTube channel was created created_month: Month when the YouTube channel was created created_date: Exact date of the YouTube channel's creation Gross tertiary education enrollment (%): Percentage of the population enrolled in tertiary education in the country Population: Total population of the country Unemployment rate: Unemployment rate in the country Urban_population: Percentage of the population living in urban areas Latitude: Latitude coordinate of the country's location Longitude: Longitude coordinate of the country's location

Potential Use Cases

YouTube Analytics: Gain valuable insights into the success factors of top YouTube channels and understand what sets them apart from the rest. Content Strategy: Discover the most popular categories and upload frequencies that resonate with audiences. Regional Influencers: Identify influential YouTube creators from different countries and analyze their impact on a global scale. Earnings Analysis: Explore the correlation between channel performance and estimated earnings. Geospatial Visualization: Visualize the distribution of successful YouTube channels on a world map and uncover geographical trends. Trending Topics: Investigate how certain categories gain popularity over time and correlate with world events.

Top 100 YouTube Channels (Updated Monthly) - ytRank.com Discover the latest ranking of the top 100 YouTube channels, updated every month. This dataset provides an up-to-date list of channels sorted by subscriber count, offering insights into the most popular creators and trending content on the platform. Stay informed about the biggest names in the YouTube community with our accurate and regularly refreshed data.

In 2024, users engaged more with the videos they watched on YouTube compared to the previous year. The number of average interactions on YouTube grew to 2.36 in the last measured year. This is an increase compared to 2023, when the number of comments, likes, and share on pieces of content hosted on YouTube was of approximately 2.1 interactions on average.

Content

This dataset contains:,

scripts_zip/scripts: Subtitles of many ads ads.json: Meta-information about ads & leaderboards, such as: * title: title of leaderboard * year: release year of leaderboard * data: [ { * rank: rank of the ad in the leaderboard * script_link: link to the subtitles of the ad * brand: brand of ad * creative agency: agency responsible for production * media agency: agency responsible for publication * title: title of ad }, ..., ... ]

Acknowledgements

Sources:

Think With Google Youtube

As of October 2025, the video-sharing platform YouTube had approximately 2.58 billion users worldwide. During the same period, an estimated 53 percent of its global audience were male.

In 2023, all the analyzed channels with an audience between 50,000 and 55 million subscribers had over 418,000 disliked on YouTube, against the approximately 17 million likes recorded in 2023. In comparison, all the tiny accounts analyzed - which had up to 500 subscribers - managed to accumulate a total of one million likes, as well as 53,600 dislikes and 41,430 comments.

Dataset for paper: Disturbed YouTube for Kids: Characterizing and Detecting Inappropriate Videos Targeting Young Children The dataset consists of five files: 1. groundtruth_videos.json: This is the ground truth dataset. We have 4797 manually annotated videos (1513 suitable, 929 disturbing, 419 restricted, and 1936 irrelevant). You can distinguish among the different labels by observing the 'classification_label' field. 2. elsagate_related_videos.json: Contains the data for 233K elsagate-related YouTube videos (1K seed and 232K recommended) that were obtained as described in the paper. 3. other_child_related_videos.json: Contains the data for 155K other child-related YouTube videos (2K seed and 153K recommended) that were obtained as described in the paper. 4. random_videos.json: Contains the data for 482K random YouTube videos (8K seed and 474K recommended) that were obtained as described in the paper. 5. popular_videos.json: Contains the data for 11K popular YouTube videos (500 seed and 10.5K recommended) that were obtained between November 18 and November 21, 2018, as described in the paper. For each video in all sets, you can check the predicted label of our classifier by observing the 'prediction' field.