Trending video data from YouTube.

Video Object Properties

This dataset represents each trending video object with the following properties:

• title: The title of the video.
• description: The video's description.
• publishedDate: The date and time when the video was published (in a machine-readable format).
• publishedText: The date and time when the video was published (in a human-readable format).
• videoId: The unique identifier for the video.
• videoUrl: The URL of the video.
• channelName: The name of the channel that published the video.
• channelId: The unique identifier for the channel.
• channelUrl: The URL of the channel.
• thumbnails: URLs for the video's thumbnail images in different resolutions.
• views: The number of views the video has received.
• viewsText: The number of views in a human-readable format (e.g., "1.2M views").
• duration: The duration of the video (in a machine-readable format).
• durationText: The duration of the video in a human-readable format (e.g., "3:24").
• verified: A boolean indicating whether the channel is verified or not.
• creatorOnRise: A boolean indicating whether the channel is marked as a "Creator on the Rise" by YouTube.
• isShort: A boolean indicating whether the video is a YouTube Shorts video or not.

trending video data is collected from various categories on YouTube:

• Default: The main YouTube trending page, featuring videos across all categories.
• Music: The trending page specifically for music videos and music-related content.
• Gaming: The trending page for gaming videos, live streams, and gaming-related content.
• Movies: The trending page for movie trailers, clips, and other movie-related videos.

The collected data is saved daily in compressed CSV (Comma-Separated Values) files, with one file per category. The file naming convention follows the format: category_**timestamp**.csv.gz

Where:

• category is the name of the category (e.g., default, music, gaming, movies).
• timestamp is the current date and time in the format YYYYMMDD (e.g., 20230501 for May 1, 2023).

What is the most subscribed YouTube Channel?

Indian music network T-Series had the most YouTube subscribers in the world as of November 2022, with 229 million users following the channel. YouTube Movies ranked second with roughly 158 million subscribers.

How many hours of video are uploaded to YouTube every minute?

YouTube was launched in 2005 as a platform for sharing user-generated videos such as vlogs, tutorials, or original series. The site grew rapidly and reportedly had 100 million video views per day and more than 65 thousand daily uploads only a year later. As of February 2020, more than 500 hours of video were uploaded to YouTube every minute, up from a mere 24 hours of content uploads per minute in 2010.

Highest earning YouTubers

In November 2022, MrBeast surpassed long-standing most subscribed YouTuber PewDiePie, having reached approximately 112 million subscribers. Due to the high number of subscribers and even higher number of views, these out-of-the-box stars not only have millions of fans, but also considerable earnings from their YouTube activities. In 2021, MrBeast was estimated to have earned around 54 million U.S. dollars, topping the ranking of the highest-earning YouTube creators.

YouTube Partner Program

In the third quarter of 2022, YouTube’s ad revenue amounted to over seven billion U.S. dollars. Through its Partner Program, YouTube also rewards uploaders of popular videos with a share of the advertising revenues the content generates. This, paired with the fact that many users of the video sharing platform tend to have favorite channels that they revisit regularly, has given rise to another phenomenon: YouTube celebrities. Although some of these well-known figures were discovered on the website but then carved a successful career outside of YouTube, for many others the site is their primary platform for delivering content and staying in contact with fans, all while signing lucrative deals or promotional partnerships

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.

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!

Context

As YouTube is now one of the biggest online earning platform for content creators, lots of new content creators join everyday and upload almost thousands of video daily, which creates enormous amount of data everyday, from which we can do lots of things. Here I have taken data of T-Series, one of the most subscribed channel on YouTube, it's views and ratings of its past video and estimate its revenue for each video.

There's a story behind every dataset and here's your opportunity to share yours.

Content

There are very less features in this dataset, namely: Date: The date when the particular video was released Name: Name of the video on YouTube Views: The views on YouTube as per December 2020 Ratings: The ratings of the video Comments: Number of comments on the video Estimated Revenue: The revenue generated by the video on YouTube What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Acknowledgements

This data search wouldn't be possible without my sister as she was constantly watching videos on YouTube which lead me to this idea and then started working on this dataset.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

How much time do people spend on social media? As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.