https://brightdata.com/licensehttps://brightdata.com/license
Use our YouTube Videos dataset to extract detailed information from public videos and filter by video title, views, upload date, or likes. Data points include video URL, title, description, thumbnail, upload date, view count, like count, comment count, tags, and more. You can purchase the entire dataset or a customized subset, tailored to your needs. Popular use cases for this dataset include trend analysis, content performance tracking, brand monitoring, and influencer campaign optimization.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
YouTube keeps track of the most popular videos that are being seen on the site. Several months' worth of daily trending YouTube video statistics are included in this data set. Data for France and the USA are included. The videos on this list are those that users have liked and have received the most views, comments, and likes from other users. These videos are then displayed on the trending page. The greatest videos are shown at the top of the page by ranking these videos according to a ratio of views, likes, comments, and shares.
This dataset is a daily record of the top trending YouTube videos.
content: Data about daily trending YouTube videos for several months, and counting, is included in this dataset. Up to 200 trending videos are published each day, with data for the US and FR regions (the USA and France, respectively) included.
As of June 2022, more than *** hours of video were uploaded to YouTube every minute. This equates to approximately ****** hours of newly uploaded content per hour. The amount of content on YouTube has increased dramatically as consumer’s appetites for online video has grown. In fact, the number of video content hours uploaded every 60 seconds grew by around ** percent between 2014 and 2020. YouTube global users Online video is one of the most popular digital activities worldwide, with ** percent of internet users worldwide watching more than ** hours of online videos on a weekly basis in 2023. It was estimated that in 2023 YouTube would reach approximately *** million users worldwide. In 2022, the video platform was one of the leading media and entertainment brands worldwide, with a value of more than ** billion U.S. dollars. YouTube video content consumption The most viewed YouTube channels of all time have racked up billions of viewers, millions of subscribers and cover a wide variety of topics ranging from music to cosmetics. The YouTube channel owner with the most video views is Indian music label T-Series, which counted ****** billion lifetime views. Other popular YouTubers are gaming personalities such as PewDiePie, DanTDM and Markiplier.
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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 February 2025, India was the country with the largest YouTube audience by far, with approximately 491 million users engaging with the popular social video platform. The United States followed, with around 253 million YouTube viewers. Brazil came in third, with 144 million users watching content on YouTube. The United Kingdom saw around 54.8 million internet users engaging with the platform in the examined period. What country has the highest percentage of YouTube users? In July 2024, the United Arab Emirates was the country with the highest YouTube penetration worldwide, as around 94 percent of the country's digital population engaged with the service. In 2024, YouTube counted around 100 million paid subscribers for its YouTube Music and YouTube Premium services. YouTube mobile markets In 2024, YouTube was among the most popular social media platforms worldwide. In terms of revenues, the YouTube app generated approximately 28 million U.S. dollars in revenues in the United States in January 2024, as well as 19 million U.S. dollars in Japan.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
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.
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.
This dataset was collected using the YouTube API. This dataset is the updated version of Trending YouTube Video Statistics.
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!
https://brightdata.com/licensehttps://brightdata.com/license
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.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains data related to most watched YouTube videos till April 2024 . This contains different columns namely views,artist,channel,etc. The data is ranked on the basis of number of views.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Here I've selected some 207 channels from Youtube and harvested their public data from the YouTube Data API v3. Considering the API's limitations and some data cleaning I've made, it has yield some 150.899 videos with the following variables:
Then I've done some interactive plots with ipywidgets for the user to enjoy exploring the data for each channel or even comparing two channels at once.
Feel free to grow and update the dataset, baring in mind the API's limitation of only 20.000 videos by channel.
*Apparently YouTube wont display the dislikes count anymore, which makes this kind of dataset even more interesting and possibly one of the last of its kind.
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YouTube Creator Statistics: YouTube is the world's largest video-sharing platform. It was launched in Feb 2005. In 2006 it was purchased by Google in 2006. As of 2024, it is the world’s second most-viewed website after Google search. YouTube has managed to create an unprecedented social impact on the world. It has been instrumental in changing the overall dynamics of social media presence.
It has been a dominant force in shaping internet trends and creating millionaire celebrities. Likewise, it would be interesting to highlight YouTube creator statistics to gain valuable information on how this video-sharing platform has profoundly impacted the internet world.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
A comprehensive dataset of over 157 up-to-date YouTube statistics for 2025, covering user behavior, demographics, creator earnings, ad performance, Shorts, and AI content trends. Compiled from credible sources such as Pew Research, Statista, eMarketer, Google, and YouTube.
The global number of Youtube users in was forecast to continuously increase between 2024 and 2029 by in total 232.5 million users (+24.91 percent). After the ninth consecutive increasing year, the Youtube user base is estimated to reach 1.2 billion users and therefore a new peak in 2029. Notably, the number of Youtube users of was continuously increasing over the past years.User figures, shown here regarding the platform youtube, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of Youtube users in countries like Africa and South America.
According to a March to April 2021 survey of U.S. parents, 70 percent of YouTube videos watched by children did not include any physical violence. However, 20 percent of videos included mild or limited physical violence, and a further 14 percent of video content consumed by children aged up to eight years had persistent themes of violence. This makes physical violence one of the most common types of negative content in YouTube videos watched by children. In contrast, drinking, drugs, or smoking was not present in 96 percent of video content that was popular with kids. Generally speaking, the great majority of the videos analyzed did not present any negative content.
This dataset was created by zd6rvteb4 3
This both the original .tfrecords and a Parquet representation of the YouTube 8 Million dataset. YouTube-8M is a large-scale labeled video dataset that consists of millions of YouTube video IDs, with high-quality machine-generated annotations from a diverse vocabulary of 3,800+ visual entities. It comes with precomputed audio-visual features from billions of frames and audio segments, designed to fit on a single hard disk. This dataset also includes the YouTube-8M Segments data from June 2019. This dataset is 'Lakehouse Ready'. Meaning, you can query this data in-place straight out of the Registry of Open Data S3 bucket. Deploy this dataset's corresponding CloudFormation template to create the AWS Glue Catalog entries into your account in about 30 seconds. That one step will enable you to interact with the data with AWS Athena, AWS SageMaker, AWS EMR, or join into your AWS Redshift clusters. More detail in (the documentation)[https://github.com/aws-samples/data-lake-as-code/blob/roda-ml/README.md.
The YouTube-100M data set consists of 100 million YouTube videos: 70M training videos, 10M evaluation videos, and 20M validation videos. Videos average 4.6 minutes each for a total of 5.4M training hours. Each of these videos is labeled with 1 or more topic identifiers from a set of 30,871 labels. There are an average of around 5 labels per video. The labels are assigned automatically based on a combination of metadata (title, description, comments, etc.), context, and image content for each video. The labels apply to the entire video and range from very generic (e.g. “Song”) to very specific (e.g. “Cormorant”). Being machine generated, the labels are not 100% accurate and of the 30K labels, some are clearly acoustically relevant (“Trumpet”) and others are less so (“Web Page”). Videos often bear annotations with multiple degrees of specificity. For example, videos labeled with “Trumpet” are often labeled “Entertainment” as well, although no hierarchy is enforced.
In 2021, YouTube's user base in the United States amounts to approximately 203.80 million users. The number of YouTube users in the United States is projected to reach 219.28 million users by 2025. User figures have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).
pavitemple/youtube-videos dataset hosted on Hugging Face and contributed by the HF Datasets community
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This is the statistics for the Top 10 songs of various spotify artists and their YouTube videos. The Creators above generated the data and uploaded it to Kaggle on February 6-7 2023. The license to use this data is "CC0: Public Domain", allowing the data to be copied, modified, distributed, and worked on without having to ask permission. The data is in numerical and textual CSV format as attached. This dataset contains the statistics and attributes of the top 10 songs of various artists in the world. As described by the creators above, it includes 26 variables for each of the songs collected from spotify. These variables are briefly described next:
Track: name of the song, as visible on the Spotify platform. Artist: name of the artist. Url_spotify: the Url of the artist. Album: the album in wich the song is contained on Spotify. Album_type: indicates if the song is relesead on Spotify as a single or contained in an album. Uri: a spotify link used to find the song through the API. Danceability: describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable. Energy: is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy. Key: the key the track is in. Integers map to pitches using standard Pitch Class notation. E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1. Loudness: the overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typically range between -60 and 0 db. Speechiness: detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value. Values above 0.66 describe tracks that are probably made entirely of spoken words. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values below 0.33 most likely represent music and other non-speech-like tracks. Acousticness: a confidence measure from 0.0 to 1.0 of whether the track is acoustic. 1.0 represents high confidence the track is acoustic. Instrumentalness: predicts whether a track contains no vocals. "Ooh" and "aah" sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly "vocal". The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0. Liveness: detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live. Valence: a measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry). Tempo: the overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration. Duration_ms: the duration of the track in milliseconds. Stream: number of streams of the song on Spotify. Url_youtube: url of the video linked to the song on Youtube, if it have any. Title: title of the videoclip on youtube. Channel: name of the channel that have published the video. Views: number of views. Likes: number of likes. Comments: number of comments. Description: description of the video on Youtube. Licensed: Indicates whether the video represents licensed content, which means that the content was uploaded to a channel linked to a YouTube content partner and then claimed by that partner. official_video: boolean value that indicates if the video found is the official video of the song. The data was last updated on February 7, 2023.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The proliferation of mobile devices with video recording capabilities has revolutionized the creation, sharing, and consumption of audiovisual content, turning user-generated video (UGV) platforms into major data sources.
Despite this growth, there is a notable gap in the availability of public datasets featuring multi-angle recordings of sports events captured by various mobile cameras. This led to the creation of the MUVY Dataset, with the name stemming from Multiview User-generated Videos from YouTube.
The dataset offers a diverse collection of sports videos from multiple perspectives, without restrictions on video size. In its first version, it covers sports like, American football, artistic gymnastics, athletics, basketball, tennis, and cricket.
The dataset addresses common challenges in user-generated videos, such as shaking, occlusions, blurring, and abrupt movements. Each video is accompanied by metadata including camera identification, YouTube URLs, extracted frames, and object annotations.
https://brightdata.com/licensehttps://brightdata.com/license
Use our YouTube Videos dataset to extract detailed information from public videos and filter by video title, views, upload date, or likes. Data points include video URL, title, description, thumbnail, upload date, view count, like count, comment count, tags, and more. You can purchase the entire dataset or a customized subset, tailored to your needs. Popular use cases for this dataset include trend analysis, content performance tracking, brand monitoring, and influencer campaign optimization.