In 2025, the brand value of YouTube stood at ***** billion U.S. dollars. A year earlier, the value was estimated at *** billion dollars. YouTube is among the most valuable media brands worldwide.

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.

In 2024, the brand value of YouTube stood at 31.7 billion U.S. dollars. A year earlier, the value was estimated at 29.7 billion dollars. YouTube is among the most valuable media brands worldwide.

In 2023, it was estimated that YouTube Mr. Beast (Jimmy Donaldson) ranked first as the top-earning YouTuber worldwide with earnings of approximately ** million U.S. dollars. Comedic duo Rhett & Link ranked second, with an estimate of ** million U.S. dollars earned during the last measured year. Fourth-ranked Ryan Kaji, who goes by Ryan on his YouTube channel, called Ryan's World, is 12 years old and earned ** million U.S. dollars in the past year, surpassing YouTuber Jake Paul. YouTube most popular channels and creators Created in 2005, YouTube has become one of the most popular social networks worldwide. In 2023, YouTube had approximately *** million users worldwide. As of February 2024, the most-subscribed YouTube channels did not only include popular video game commentators or comedy creators, but also children-specific channels, such as nursery rhymes channel Cocomelon, Kids Diana Show, and Like Nastya. Beauty and skincare YouTubers were also among the most beloved content creators for users on the social video platforms, with channels such as Sandra Cires Art and Jeffree Star recording over ** million subscribers as of March 2024. Content for children In 2023, U.S. children were estimated to have spent over ** minutes per day on average watching YouTube content. Despite being based on user-generated content such as make-up tutorials, toy reviews, or comedy sketches, YouTube channels for kids present professional video production values and full-time work commitment to the platform. As of March 2024, Cocomelon had over ***** billion views, while the Kids Diana Show had over *** billion views.

A dataset of Youtube advertising value and purchase intentions of young Vietnamese customers

In the first quarter of 2023, brands and companies that activated sponsored YouTube campaigns with the YouTuber Philip DeFranco - sxephil - saw over 4.42 million U.S. dollars during the first quarter of 2023 in IMV due to collaboration with brands such as Greens, Bokksu, Grammarly, NordVPN and others.

As of January 2025, the ranking of the most popular YouTube channels based on monthly views is dominated by music and children's content. Wiz Khalifa's Music channel was ranked first with a whopping six billion channel views, while Wow Kidz ranked second with over five billion video views in the last examined month. Indian music record channel T-Series -which ranked first continuously in 2021 and 2022, placed third with 2.72 billion video views. Most subscribed YouTube channels When looking at the most-subscribed YouTube channels: Indian music label T-Series was ranked first with 229 million channel subscribers. The video game commentator Felix Kjellberg, aka PewDiePie, ranked seventh, with roughly 111 million subscribers, after being surpassed by Jimmy Donaldson, aka MrBeast in November 2022. As of June 2022, PewDiePie was still the most subscribed gaming-content channel on YouTube, followed by Salvadorian YouTuber Fernanfloo with 45 million global subscribers. Creators' earnings MrBeast was the highest-earning YouTuber in 2021, with 54 million U.S. dollars. Ryan Kaji from Ryan's World was among the youngest content creators making the rankings of the highest-earning YouTubers in 2021, with an estimated revenue of 27 million U.S. dollars. Ryan’s channel was set up by his parents in March 2015, when the young content creator was three years old. MrBeast was also the leading content creator on YouTube based on Influence Media Value, while PewDiePie ranked third with an evaluation of around 3.91 million U.S. dollars.

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.

This dataset provides estimated YouTube RPM (Revenue Per Mille) ranges for different niches in 2025, based on ad revenue earned per 1,000 monetized views.

This dataset contains two files for analyzing the relationship between the popularity of a certain video and the most relevant/liked comments of said video.

File Descriptions videos-stats.csv: This file contains some basic information about each video, such as the title, likes, views, keyword, and comment count.

comments.csv: For each video in videos-stats.csv, comments.csv contains the top ten most relevant comments as well as said comments' sentiments and likes.

Column Descriptions videos-stats.csv:

Title: Video Title. Video ID: The Video Identifier. Published At: The date the video was published in YYYY-MM-DD. Keyword: The keyword associated with the video. Likes: The number of likes the video received. If this value is -1, the likes are not publicly visible. Comments: The number of comments the video has. If this value is -1, the video creator has disabled comments. Views: The number of views the video got. comments.csv:

Video ID: The Video Identifier. Comment: The comment text. Likes: The number of likes the comment received. Sentiment: The sentiment of the comment. A value of 0 represents a negative sentiment, while values of 1 or 2 represent neutral and positive sentiments respectively. Applicability Sentiment Analysis with comments Text Generation with comments Predicting video likes from comment information Popularity Analysis by Keyword Popularity Analysis Prediction video views from comment information/video statistics In-depth EDA of the Data

Original Data Source: Youtube Statistics

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.

As of March 2025, YouTube recorded a market share value of 0.37 percent in Hungary. Over the period under consideration, the highest value was recorded at 1. 57 percent.

Comparison of YouTube Shorts vs Long-Form videos in terms of RPM, ad placement, revenue model, and monetization efficiency.

Video object segmentation has been studied extensively in the past decade due to its importance in understanding video spatial-temporal structures as well as its value in industrial applications. Recently, data-driven algorithms (e.g. deep learning) have become the dominant approach to computer vision problems and one of the most important keys to their successes is the availability of large-scale datasets. Previously, we presented the first large-scale video object segmentation dataset named YouTubeVOS and hosted the Large-scale Video Object Segmentation Challenge in conjuction with ECCV 2018, ICCV 2019 and CVPR 2021. This year, we are thrilled to invite you to the 4th Large-scale Video Object Segmentation Challenge in conjunction with CVPR 2022. The benchmark would be an augmented version of the YouTubeVOS dataset with more annotations. Some incorrect annotations are also corrected. For more details, check our website for the workshop and challenge.

The average minimum price of a sponsored YouTube video with more than one million views was ***** U.S. dollars in 2022. The average minimum price of a sponsored video with *** thousand to one million views was ***** U.S. dollars, while the average maximum price was ****** U.S. dollars.

As of January 2025, Thibaud Delapart Mazăre, known as Tibo InShape had the most popular YouTube channel in France, with almost 26 million subscribers. Second-ranked YouTuber Squeezie had approximately 19.3 million subscribers, while the popular music channel Lofi Girl ranked third, with 14.7 million subscribers. YouTube usage in France  As of July 2024, YouTube saw almost 50.2 million active YouTube users in France, reporting a reach of over 86 percent among the French digital population. In 2023, French YouTube users engaged with the platform to find music and video content, with the terms "musique" and "film" reporting the highest index value among all examined queries. Mobile video consumption   In 2023, French users were more likely to consume digital video content on their smartphones than on laptops or Smart TVs, a sign that mobile video is becoming an increasingly popular format in the country. In 2024, mobile users in France spent almost 17 hours per month on the video sharing platform. In the second quarter of 2022, the YouTube mobile app was downloaded over 600 thousand times by iOS users, indicating the continued popularity of the app.

The statistic shows the price consumers are willing to pay for YouTube in the United States as of October 2017, sorted by ethnicity. During a survey, ** percent of Hispanic consumers stated that they would be willing to pay less than **** U.S. dollars per month for the online streaming service.

In the last quarter of 2020, the YouTube influencer media value (IMV) of brands and companies from tech, gaming, food & drink, beauty, and fashion industries that activated YouTube campaigns with sponsored content achieving at least 10,000 views stood at ****** million U.S. dollars. The IMV for the entire 2020 across all industries amounted to **** billion U.S. dollars.

This dataset provides YouTube video metadata, suitable for practising text classification using Natural Language Processing (NLP) techniques. It includes video IDs, titles, descriptions, and categories, making it a valuable resource for those looking to apply and refine their NLP skills. The dataset was generated by scraping YouTube, offering a real-world scenario for data cleaning and analysis, including challenges such as missing values and class imbalance.

Columns

• Video ID: A unique identifier for each YouTube video. Note that this column contains some missing data.
• title: The title of the YouTube video.
• description: The textual description associated with the YouTube video.
• category: The category under which the video was classified when scraped.
• link: A direct URL to the YouTube video.

Distribution

The dataset is typically provided in a CSV file format. It contains approximately 3,400 video records, derived from an initial scrape of 3,600 videos. The dataset is known to be untidy, featuring missing values and imbalanced classes across its categories, presenting an opportunity for data cleaning and preprocessing exercises.

Usage

This dataset is ideally suited for: * Practising basic text classification using various NLP techniques. * Learning how to handle common data issues such as missing values and imbalanced classes. * Developing and applying data cleaning and preprocessing methods. * Experimenting with different machine learning algorithms for text analysis.

Coverage

The dataset has a global reach, as it comprises YouTube videos accessible worldwide. It was listed on 08/06/2025. The video categories included in the dataset were specifically queried across four main areas: Travel Vlogs, Food, Art and Music, and History. Users should be aware that the data includes missing values and exhibits class imbalance across these categories.

License

CCO

Who Can Use It

This dataset is intended for individuals and researchers, particularly those at an intermediate skill level, who wish to practise and improve their text classification and NLP capabilities. It is also highly beneficial for anyone looking to gain practical experience in data cleaning, handling missing data, and addressing class imbalance in real-world datasets.

Dataset Name Suggestions

• YouTube Video Classification Data
• NLP YouTube Metadata Dataset
• YouTube Content Classification Dataset
• Video Description Text Analysis Dataset

Attributes

Original Data Source: Youtube Videos Dataset (~3400 videos)

YouTube had a market share among social media platforms in Portugal of *** percent in February 2022. A year later, its market share was practically the same. By January 2025, it was more than **** percent. The highest value registered over the considered period was **** percent, which occurred in August 2024.