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...

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.

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.

YouTube is the world's largest video-sharing platform, launched in 2005. It allows users to upload, view, and share videos, and has grown to be a central hub for content creators across various fields, including entertainment, education, music, and more. With over 2 billion logged-in users monthly, YouTube has become an essential platform for digital content and marketing.

The Top 1000 YouTube Channels Dataset captures detailed information about the top-performing YouTube channels globally. This dataset includes the following columns:

• Rank : The ranking of the YouTube channel based on its overall popularity and performance.
• Youtuber : The name of the YouTuber or the title of the YouTube channel.
• Subscribers : The total number of subscribers to the channel, indicating its reach and popularity.
• Video Views : The total number of video views the channel has accumulated, reflecting its engagement and audience interaction.
• Video Count : The total number of videos uploaded by the channel, showing the content volume produced.
• Category : The genre or category the channel belongs to, such as music, education, entertainment, etc.
• Started : The year the channel was created, providing insight into its longevity and growth over time.

This dataset is invaluable for analyzing trends, understanding content strategies, and benchmarking channel performances within the YouTube ecosystem.

This dataset contains anonymized logs of user-level YouTube viewing activity, collected via Amazon Mechanical Turk. Each user in the dataset provided at least six months of their YouTube watch history, enabling longitudinal analysis of personal viewing patterns.

Each row in the dataset represents a single watch event and includes metadata such as: - the video ID - watch timestamp - whether the user was subscribed to the channel at the time - and whether the video was part of a playlist

This dataset is intended to support research in user behavior modeling, content recommendation systems, temporal video engagement, and personalized analytics.

The dataset accompanies the paper:

"A YouTube dataset with user-level usage data: Baseline characteristics and key insights"
Authors: Shruti Lall, Mohit Agarwal, Raghupathy Sivakumar
Conference: IEEE ICC 2020 – International Conference on Communications

If you use this dataset in your research, please cite the paper above.

As of February 2025, ** percent of the YouTube global audience was composed of male users aged between 25 and 34 years, as well as around *** percent of female users of the same age. Male users aged between 35 and 44 years on the platform accounted for **** percent of the total, while women of the same age using YouTube had an audience share of *** percent in the examined period. YouTube’s global popularity The number of monthly active users on YouTube reached almost *** 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 *** million, while the United States recorded a YouTube audience of around *** million users.

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

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.

USA

Panda Shorts, a channel that focuses on comedy reactions, was the most viewed channel on YouTube in Sweden, as of January 2025. The videos, focused mainly on reactions and challenges, were viewed over **** billion times. The next channel in the ranking was Avicii, with more than **** billion views. This was followed with another channel dedicated to Avicii, and AviciiOfficialVEVO had around **** billion video views for the evaluated period. Furthermore, Panda Shorts had the channel with the highest number of subscribers, reaching over **** million in January 2025. Among the other Swedish YouTube channels with the most subscribers, were ABBA and Family Playlab.  How much do YouTubers in Sweden earn? A study, conducted in 2020, analyzed the YouTubers in Sweden, by their influence and income. A so-called micro influencer would make minimum ************* Swedish kronor per video, while a macro influencer would make between ** thousand and ** thousand that year. An icon influencer could make up to *** thousand Swedish kronor.  YouTube activities Watching entertaining videos was what most Swedes used YouTube for in 2022. Other popular activities were watching educational videos, listening to music, watching documentaries, and subscribing to channels. Three percent of the respondents in 2022, said, they created and published their own videos.

The dataset contains data about 100 videos and 18211 their Russian comments from Youtube on the first aid topic. The dataset will be useful for opinion mining with the help of the natural language processing.

Dataset

This dataset was created by auroraB

Contents

The file contains the names of all YouTube videos that were evaluated in the survey, along with their corresponding access links (for the paper - accessed occurred in March 2020), and the number of shares up to that date.

Extensive Creator Coverage: Our dataset includes a diverse range of YouTube content creators, spanning various genres, subscriber counts, and regions. Access information on creators from a wide spectrum of content categories.

Creator Profiles: Explore detailed creator profiles, including biographies, subscriber counts, video counts, and contact information.

Customizable Data Delivery: The dataset is available in flexible formats, such as CSV, JSON, or API integration, allowing seamless integration with your existing data infrastructure. Customize the data to meet your specific research and analysis needs.

USA

The number of Youtube users in India was forecast to continuously increase between 2024 and 2029 by in total 222.2 million users (+34.88 percent). After the ninth consecutive increasing year, the Youtube user base is estimated to reach 859.26 million 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 Sri Lanka and Nepal.

Krish Naik's YouTube channel is a dynamic and informative platform dedicated to the fields of Data Science, Machine Learning, and Artificial Intelligence. With a focus on providing both theoretical knowledge and practical insights, the channel caters to a wide audience ranging from beginners to advanced practitioners in the tech field.

1) Data Introduction • The YouTube Clickbait Classification dataset consists of video titles and statistics aimed at classifying videos as clickbait or not clickbait. This dataset includes attributes such as video ID, title, views, likes, dislikes, and favorites, providing a basis for binary classification tasks to identify misleading content.

2) Data Utilization (1) YouTube Clickbait data has characteristics that: • It includes detailed statistics for each video, such as views, likes, dislikes, and favorites, alongside the video titles. This information helps in understanding the engagement metrics and identifying patterns associated with clickbait content. (2) YouTube Clickbait data can be used to: • Content Analysis: Assists in developing models to classify videos as clickbait or not, helping in curating quality content and improving user experience on video platforms. • Marketing and SEO: Supports the development of strategies to enhance video reach and engagement while avoiding deceptive practices, aiding in ethical content marketing and search engine optimization.

This dataset contains English-language comments extracted from YouTube video-sharing platform (YouTube LLC, California, USA) in November 2022. The comments were collected as follows: (1) Titles of the first aid-related videos found on YouTube with a “first aid” keyword were screened, and videos potentially providing instructions on how to administer first aid in a health emergency situation were selected (n=104); (2) all comments to the videos (n=16,091) were automatically extracted using the web scraping technique based on a Python script developed by the authors; (3) non-English, duplicate and apparently irrelevant comments and comment replies were excluded (n=15,390). Eventually, a total of 701 comments composed the dataset.

This dataset contains all comments (comments and replies) of the YouTube vision video "Tunnels" by "The Boring Company" fetched on 2020-10-13 using YouTube API. The comments are classified manually by three persons. We performed a single-class labeling of the video comments regarding their relevance for requirement engineering (RE) (ham/spam), their polarity (positive/neutral/negative). Furthermore, we performed a multi-class labeling of the comments regarding their intention (feature request and problem report) and their topic (efficiency and safety). While a comment can only be relevant or not relevant and have only one polarity, a comment can have one or more intentions and also one or more topics.

For the replies, one person also classified them regarding their relevance for RE. However, the investigation of the replies is ongoing and future work.

Remark: For 126 comments and 26 replies, we could not determine the date and time since they were no longer accessible on YouTube at the time this data set was created. In the case of a missing date and time, we inserted "NULL" in the corresponding cell.

This data set includes the following files:

Dataset.xlsx contains the raw and labeled video comments and replies:

For each comment, the data set contains:

ID: An identification number generated by YouTube for the comment

Date: The date and time of the creation of the comment

Author: The username of the author of the comment

Likes: The number of likes of the comment

Replies: The number of replies to the comment

Comment: The written comment

Relevance: Label indicating the relevance of the comment for RE (ham = relevant, spam = irrelevant)

Polarity: Label indicating the polarity of the comment

Feature request: Label indicating that the comment request a feature

Problem report: Label indicating that the comment reports a problem

Efficiency: Label indicating that the comment deals with the topic efficiency

Safety: Label indicating that the comment deals with the topic safety

For each reply, the data set contains:

ID: The identification number of the comment to which the reply belongs

Date: The date and time of the creation of the reply

Author: The username of the author of the reply

Likes: The number of likes of the reply

Comment: The written reply

Relevance: Label indicating the relevance of the reply for RE (ham = relevant, spam = irrelevant)

Detailed analysis results.xlsx contains the detailed results of all ten times repeated 10-fold cross validation analyses for each of all considered combinations of machine learning algorithms and features

Guide Sheet - Multi-class labeling.pdf describes the coding task, defines the categories, and lists examples to reduce inconsistencies and increase the quality of manual multi-class labeling

Guide Sheet - Single-class labeling.pdf describes the coding task, defines the categories, and lists examples to reduce inconsistencies and increase the quality of manual single-class labeling

Python scripts for analysis.zip contains the scripts (as jupyter notebooks) and prepared data (as csv-files) for the analyses

Analysis of ‘Abonnés sur Youtube’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/5e3ca90bdee7e75771f5c8eb on 11 January 2022.

--- Dataset description provided by original source is as follows ---

Ce jeu de données présente le nombre d'abonnés sur les comptes des chaînes YouTube des entités du Groupe BPCE

--- Original source retains full ownership of the source dataset ---