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.

Dataset Name: 2023 YouTube Most Viewed Top600

Description: This dataset, titled "2023YouTubeMostViewed_Top600", comprises a curated selection of the top 600 YouTube videos based on view count, specifically from the year 2023. Each entry in the dataset represents a unique video, encompassing several key metrics:

• Title: The title of the video, providing a glimpse into its content.
• Published At: The upload date and time of the video, confirming its recency within the 2023 timeframe.
• Duration: The length of the video, indicating its watch time.
• View Count: The total number of views the video has accumulated, the primary metric for its inclusion in this dataset.
• Like Count: The number of likes the video has received, offering insight into viewer engagement.
• Comment Count: The total count of comments on the video, further reflecting audience interaction.

It's important to note that while these videos are among the most viewed as of the data retrieval date, the landscape of YouTube is dynamic. View counts are continually changing, and what constitutes the 'most viewed' can fluctuate. Thus, the dataset should be seen as a snapshot of popularity and viewer engagement during a specific period in 2023, rather than an absolute ranking. This dataset is invaluable for analysis of trending content, viewer preferences, and video engagement metrics on YouTube for the year 2023.

Note: Ethically mined data from YouTube

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...

YouTube Videos and Channels Metadata

Analyze the statistical relation between videos and form a topic tree

By VISHWANATH SESHAGIRI [source]

About this dataset

This dataset contains YouTube video and channel metadata to analyze the statistical relation between videos and form a topic tree. With 9 direct features, 13 more indirect features, it has all that you need to build a deep understanding of how videos are related – including information like total views per unit time, channel views, likes/subscribers ratio, comments/views ratio, dislikes/subscribers ratio etc. This data provides us with a unique opportunity to gain insights on topics such as subscriber count trends over time or calculating the impact of trends on subscriber engagement. We can develop powerful models that show us how different types of content drive viewership and identify the most popular styles or topics within YouTube's vast catalogue. Additionally this data offers an intriguing look into consumer behaviour as we can explore what drives people to watch specific videos at certain times or appreciate certain channels more than others - by analyzing things like likes per subscribers and dislikes per views ratios for example! Finally this dataset is completely open source with an easy-to-understand Github repo making it an invaluable resource for anyone looking to gain better insights into how their audience interacts with their content and how they might improve it in the future

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

How to Use This Dataset

In general, it is important to understand each parameter in the data set before proceeding with analysis. The parameters included are totalviews/channelelapsedtime, channelViewCount, likes/subscriber, views/subscribers, subscriberCounts, dislikes/views comments/subscriberchannelCommentCounts,, likes/dislikes comments/views dislikes/ subscribers totviewes /totsubsvews /elapsedtime.

To use this dataset for your own analysis:1) Review each parameter’s meaning and purpose in our dataset; 2) Get familiar with basic descriptive statistics such as mean median mode range; 3) Create visualizations or tables based on subsets of our data; 4) Understand correlations between different sets of variables or parameters; 5) Generate meaningful conclusions about specific channels or topics based on organized graph hierarchies or tables.; 6) Analyze trends over time for individual parameters as well as an aggregate reaction from all users when videos are released

Research Ideas

• Predicting the Relative Popularity of Videos: This dataset can be used to build a statistical model that can predict the relative popularity of videos based on various factors such as total views, channel viewers, likes/dislikes ratio, and comments/views ratio. This model could then be used to make recommendations and predict which videos are likely to become popular or go viral.

• Creating Topic Trees: The dataset can also be used to create topic trees or taxonomies by analyzing the content of videos and looking at what topics they cover. For example, one could analyze the most popular YouTube channels in a specific subject area, group together those that discuss similar topics, and then build an organized tree structure around those topics in order to better understand viewer interests in that area.

• Viewer Engagement Analysis: This dataset could also be used for viewer engagement analysis purposes by analyzing factors such as subscriber count, average time spent watching a video per user (elapsed time), comments made per view etc., so as to gain insights into how engaged viewers are with specific content or channels on YouTube. From this information it would be possible to optimize content strategy accordingly in order improve overall engagement rates across various types of video content and channel types

Acknowledgements

If you use this dataset in your research, please credit the original authors.

Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: YouTubeDataset_withChannelElapsed.csv | Column name | Description | |:----------------------------------|:-------------------------------------------------------| | totalviews/channelelapsedtime | Ratio of total views to channel elapsed time. (Ratio) | | channelViewCount | Total number of views for the channel. (Integer) | | likes/subscriber ...

🎙️ YouTube Transcripts Dataset

Created by SN13(, powered by Bittensor

This dataset provides high-quality transcripts from 26,241 public YouTube videos, meticulously collected and formatted for research and development in natural language processing (NLP), summarization, and language modeling.

  📦 Dataset Summary

Total Videos: 26,241 Total Hours: ~6,886.84 Language Coverage: Multilingual with translation to English(details below) Storage Format:… See the full description on the dataset page: https://huggingface.co/datasets/arrmlet/data-universe-youtube-1.

In 2023, YouTube Shorts was estimated to have around 153 million monthly viewers in the United States. Launched in 2021, Shorts have quickly become a popular format for both YouTube users and creators, with the company reporting two billon global monthly active viewers in July 2023. The format is estimated to reach 185 million U.S. viewers per month by 2026.

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.

192 YouTube Channel Views Count

This project compiles and analyzes data from 192 YouTube channels, totaling approximately 166,411 videos. The dataset includes information such as video titles, view counts, publish dates, and authors.

  Introduction

The 192 YouTube Channel Views Count project aims to provide insights and analytics on video performance across 192 different YouTube channels. By aggregating data such as video titles, view counts, publish dates, and authors… See the full description on the dataset page: https://huggingface.co/datasets/leodeveloper2000/192-Youtube-Channel-Views-Count.

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

YouTube Music Hits Dataset

A collection of YouTube music video data sourced from Wikidata, focusing on videos with significant viewership metrics.

  Dataset Description





  Overview

24,329 music videos View range: 1M to 5.5B views Temporal range: 1977-2024

  Features

youtubeId: YouTube video identifier itemLabel: Video/song title performerLabel: Artist/band name youtubeViews: View count year: Release year genreLabel: Musical genre(s)

  View… See the full description on the dataset page: https://huggingface.co/datasets/akbargherbal/youtube-music-hits.

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.

The dataset is in .xlsx format and contains four sheets: 1. A description of the variables in the other sheets 2. YouTube videos and associated metrics 3. The most frequently occuring words in the comment text 4. The most frequently occuring emojis in the comment text

Dataset for ShawGPT, a fine-tuned data science YouTube comment responder. Video link: coming soon! Blog link: coming soon!

English Audio Dataset from YouTube

This dataset contains English audio segments and creator uploaded transcripts (likely higher quality) extracted from various YouTube channels, along with corresponding transcript metadata. The data is intended for training automatic speech recognition (ASR) models.

  Data Source and Processing

The data was obtained through the following process:

Download: Audio (.m4a) and available English subtitles (.srt for en, en.j3PyPqV-e1s) were… See the full description on the dataset page: https://huggingface.co/datasets/OrcinusOrca/YouTube-English.

The data was collected from the famous cookery Youtube channels in India. The major focus was to collect the viewers' comments in Hinglish languages. The datasets are taken from top 2 Indian cooking channel named Nisha Madhulika channel and Kabita’s Kitchen channel.

Both the datasets comments are divided into seven categories:-

Label 1- Gratitude

Label 2- About the recipe

Label 3- About the video

Label 4- Praising

Label 5- Hybrid

Label 6- Undefined

Label 7- Suggestions and queries

All the labelling has been done manually.

Nisha Madhulika dataset:

Dataset characteristics: Multivariate

Number of instances: 4900

Area: Cooking

Attribute characteristics: Real

Number of attributes: 4

Date donated: March, 2019

Associate tasks: Classification

Missing values: Null

Kabita Kitchen dataset:

Dataset characteristics: Multivariate

Number of instances: 4900

Area: Cooking

Attribute characteristics: Real

Number of attributes: 4

Date donated: March, 2019

Associate tasks: Classification

Missing values: Null

There are two separate datasets file of each channel named as preprocessing and main file .

The files with preprocessing names are generated after doing the preprocessing and exploratory data analysis on both the datasets. This file includes:

• Id
• User
• Comment text
• Labels

• Count of stop-words
• Uppercase words
• Hashtags
• Word count
• Char count
• Average words
• Numeric

The main file includes:

• Id
• user
• comment text
• Labels

Youtube Title & Descriptions Dataset

  About

4941 videos across 50 YouTube Channels List of sampled channels here

  Splits:

Train: 4199 Validation: 493 Test: 249

Data was shuffled and sampled evenly from all channels to create splits. Additionally, has a column ready to go for gemma-2-9b-it fine tuning formatting! Potentially more model formats to come.

  About the Data:




  Label
  Description


  channel_name
  The… See the full description on the dataset page: https://huggingface.co/datasets/AdamLucek/youtube-titles.

YouTube Trending Videos Dataset

Exploring YouTube Trending Videos

By dskl [source]

About this dataset

Moreover it also reveals various engagement metrics such as the number of views the video has received, likes and dislikes it has garnered from viewership. Additionally information related to comment count on particular videos enables analysis regarding viewer interaction and response. Furthermore this dataset describes whether comments or ratings are disabled for a particular video allowing examination into how these factors impact engagement.

By exploring this dataset in-depth marketers can gain valuable insights into identifying trends in content popularity across different countries while taking into account timing considerations based on published day of week. It also opens up avenues for analyzing public sentiment towards specific videos based on likes vs dislikes ratios and comment count which further aids in devising suitable marketing strategies.

Overall,this informative dataset serves as an invaluable asset for researchers,data analysts,and marketers alike who strive to gain deeper understanding about trending video patterns,relevant metrics influencing content virality,factors dictating viewer sentiments,and exploring new possibilities within digital marketing space leveraging YouTube's wide reach

How to use the dataset

How to Use This Dataset: A Guide

In this guide, we will walk you through the different columns in the dataset and provide insights on how you can explore the popularity and engagement of these trending videos. Let's dive in!

Column Descriptions:

• title: The title of the video.
• channel_title: The title of the YouTube channel that published the video.
• publish_date: The date when the video was published on YouTube.
• time_frame: The duration of time (e.g., 1 day, 6 hours) that the video has been trending on YouTube.
• published_day_of_week: The day of week (e.g., Monday) when the video was published.
• publish_country: The country where the video was published.
• tags: The tags or keywords associated with the video.
• views: The number of views received by a particular video
• likes: Number o likes received per each videos
• dislike: Number dislikes receives per an individual vidoe 11.comment_count: number of comments

Popular Video Insights:

To gain insights into popular videos based on this dataset, you can focus your analysis using these columns:

title, channel_title, publish_date, time_frame, and** publish_country**.

By analyzing these attributes together with other engagement metrics such as views ,likes,**dislikes,**comments),comment_count you can identify trends in what type content is most popular both globally or within specific countries.

For instance: - You could analyze which channels are consistently publishing trending videos - Explore whether certain types of titles or tags are more likely to attract views and engagement. - Determine if certain days of the week or time frames have a higher likelihood of trending videos being published.

Engagement Insights:

To explore user engagement with the trending videos, you can focus your analysis on these columns:

likes, dislikes, comment_count

By analyzing these attributes you can get insights into how users are interacting with the content. For example: - You could compare the like and dislike ratios to identify positively received videos versus those that are more controversial. - Analyze comment counts to understand how users are engaging with the content and whether comments being disabled affects overall

Research Ideas

• Analyzing the popularity and engagement of trending videos: By analyzing the number of views, likes, dislikes, and comments, we can understand which types of videos are popular among YouTube users. We can also examine factors such as comment count and ratings disabled to see how viewers engage with trending videos.
• Understanding video trends across different countries: By examining the publish country column, we can compare the popularity of trending videos in different countries. This can help content creators or marketers understand regional preferences and tailor their content strategy accordingly.
• Studying the impact of video attributes on engagement: By exploring the relationship between video attributes (such as title, tags, publish day) and engagement metrics (views, likes), we can identify patterns or trends that influence a video's success on YouTube. This information can be...

The global number of Youtube users in was forecast to continuously increase between 2024 and 2029 by in total ***** million users (+***** percent). After the ninth consecutive increasing year, the Youtube user base is estimated to reach *** 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 *** 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.

Malaysian Youtube

Malaysian and Singaporean youtube channels, total up to 60k audio files with total 18.7k hours. URLs data at https://github.com/mesolitica/malaya-speech/tree/master/data/youtube/data Notebooks at https://github.com/mesolitica/malaya-speech/tree/master/data/youtube

  How to load the data efficiently?

import pandas as pd import json from datasets import Audio from torch.utils.data import DataLoader, Dataset

chunks = 30 sr = 16000

class Train(Dataset):… See the full description on the dataset page: https://huggingface.co/datasets/malaysia-ai/malaysian-youtube.

BackgroundInfant vaccinations are necessary for public health, but are painful, causing distress to the infant and caregivers. Breastfeeding and sucrose effectively reduce infants’ pain during vaccinations, and these strategies are recommended in health care provider (HCP)-targeted education and vaccination pain guidelines. However studies show these strategies are infrequently used. YouTube is a popular medium to publicly share and watch videos, and many consumer posted YouTube videos show distressed infants being vaccinated with no pain treatment. The aims of this study were to evaluate the reach and impact of a consumer-targeted YouTube video demonstrating use of effective pain reduction strategies during infant vaccinations.MethodsA brief consumer-targeted video showing two infants being vaccinated was posted onto YouTube on October 2013. One infant was breastfed and another infant received sucrose by mouth before and during the injection. A link to a viewer survey was visible on a banner near the end of the video. An intensive strategically planned knowledge dissemination strategy using the media, social media and messages to professional organizations took place to promote the video. Data analysis of the viewer survey, YouTube analytics of the reach of the video in terms of number of views, country of viewers, and comments relating to the video took place 12 months after the video was posted.ResultsTwelve months after posting, the video had 65,478views, 68 comments, 245 likes, 17 dislikes, and 90 shares. Average duration of viewer time was 65% of the video. The viewer survey was completed by 156 (0.24%) viewers; 90 (58%) answered as HCPs and 66 (42%) as parents. Survey results showed that the video was persuasive; intent to use or support breastfeeding or sucrose was high in both parents and HCPs after viewing the video. Comments posted were often emotional in nature, and were related to anti-vaccination (n = 26, 38%); effectiveness or positive personal experiences (n = 21, 32%); research team comments or promotion (n = 12, 18%); pro-vaccination (n = 6, 8%) and barriers to using breastfeeding or sucrose during vaccinations (n = 3, 4%).ConclusionThe video posted onto YouTube demonstrating effective pain treatment during infant vaccinations was viewed by large numbers of people around the world, however the response rate to the linked survey was extremely low. Using YouTube videos for knowledge dissemination has an extensive reach, however it is difficult to evaluate impact on behaviours and practices.