43 datasets found
  1. YouTube users worldwide 2020-2029

    • statista.com
    Updated Jul 7, 2025
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    Statista (2025). YouTube users worldwide 2020-2029 [Dataset]. https://www.statista.com/forecasts/1144088/youtube-users-in-the-world
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    Dataset updated
    Jul 7, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    YouTube, Worldwide
    Description

    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.

  2. COVID 19 - initial spread with metadata by country

    • kaggle.com
    Updated May 12, 2020
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    Kristof Boghe (2020). COVID 19 - initial spread with metadata by country [Dataset]. https://www.kaggle.com/kboghe/covid-19-initial-spread-with-metadata-by-country/tasks
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 12, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Kristof Boghe
    Description
    • I've downloaded and wrangled the John Hopkins dataset on the number of reported COVID-19 cases by country.
    • I joined this dataset with a bunch of additional metadata on country-level.

    The data only covers the period Jan. 22 - March 23, but it should be a piece of cake to apply the metadata provided here on a larger range of data (just perform a join operation).

    I used the dataset for an online lecture on data visualization --> https://www.youtube.com/watch?v=l85l1qmosEU

    The additional variables provided here could shed some light on correlational relations between - for example - the share of government expenditure in the health care system and the growth rate of the virus in a given country.

    • Data sources:

    --> Reported COVID-19 cases by country by day: https://github.com/CSSEGISandData/COVID-19 --> Data on health expenditure comes from WHO: https://apps.who.int/nha/database/Select/Indicators/en (created my own table) --> Population data and other socio-demographic data: https://www.worldometers.info/world-population/population-by-country/ --> Countries divided by continent: https://www.worldometers.info/geography/7-continents/

    • Methodology:
    1. John Hopkins data was sometimes inconsistent in their level of aggregation; reporting country-level data in most cases, but sometimes opting for county/state level data (e.g. for the United States). I aggregated all data to country-level. Moreover, there were plenty of inconsistencies in country notation between the different datasets, which required some fuzzy matching techniques.
    2. I melted the data so that one line corresponds with one day in a particular country. This is the default data scheme for anyone trying to do some data viz on the dataset at hand (I sacrifice data size for convenience here, I know...)

    Some of the interactive dashboards created with this data:

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F2342187%2F2d8e73336e269038f06b43f81183fd87%2Fcovid19%20dashboard.JPG?generation=1597334049308430&alt=media" alt="">

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F2342187%2Ff08488ae7bded1f5850e730b87437782%2Fcovid19%20dashboard%202.JPG?generation=1597334070819173&alt=media" alt="">

    Have fun!

  3. YouTube users in India 2020-2029

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). YouTube users in India 2020-2029 [Dataset]. https://www.statista.com/forecasts/1146150/youtube-users-in-india
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    The number of Youtube users in India 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 ****** 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 *** 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.

  4. 🇺🇸 Charlie Kirk(†) Twitter/ 𝕏 Dataset

    • kaggle.com
    Updated Sep 28, 2025
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    BwandoWando (2025). 🇺🇸 Charlie Kirk(†) Twitter/ 𝕏 Dataset [Dataset]. http://doi.org/10.34740/kaggle/ds/8259158
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 28, 2025
    Dataset provided by
    Kaggle
    Authors
    BwandoWando
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Who is Charlie Kirk?

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2F9ff49a3bb052e339eb85a66dca611f6c%2Fcharlie-kirk-turning-point2-91025-91025-a19b6183557949938f0dc01df2c33a28.jpg?generation=1757731111497297&alt=media" alt="">

    Charles James Kirk (October 14, 1993 – September 10, 2025) was an American conservative political activist, author, and media personality. He co-founded the organization Turning Point USA (TPUSA) in 2012 and was its executive director. He was the chief executive officer of Turning Point Action (TPAction) and a member of the Council for National Policy (CNP). In his later years, he was one of the most prominent voices of the populist MAGA movement and exemplified the growth of Christian nationalism in the Republican Party.

    From: https://en.wikipedia.org/wiki/Charlie_Kirk

    CBS News' "Who was Charlie Kirk?"

    https://www.youtube.com/watch?v=0xngCgJnO5E" alt="">

    Death

    On September 10, 2025, while on stage at Utah Valley University in Orem, Utah, for a TPUSA event, "The American Comeback Tour", Kirk was fatally shot in the neck. The shooting took place at 12:23 p.m. MDT (18:23 UTC), around 20 minutes after the event began, in front of an audience of about 3,000 people.

    From: https://en.wikipedia.org/wiki/Charlie_Kirk

    Coverage of this Dataset

    • I queried tweets with either #CharlieKirk or "Charlie Kirk" in them within the last 36 hours.

    Important Note

    • All tagged usernames (ex: @username) and forms of Ids are obfuscated and replaced with a unique hashid value based on original value retaining data integrity
    • Tagged usernames that have been banned, suspended, or deleted from the platform are still obfuscated

    "Well-known" authors

    I added a file to denote users who have posted tweets about the topic that have either characteristic(s) - Blue-certified accounts with at least 10K followers - Non-Blue-certified accounts with at least 50K followers

    This is to help map back and include additional context on who these users that are being tagged or are creating the tweets

    Source

    I signed up for a trial with https://twitterapi.io/ , check it out!

    Image

    Credit : OLIVIER TOURON/ AFP via Getty

  5. O

    YouCook

    • opendatalab.com
    zip
    Updated Mar 22, 2023
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    State University of New York (2023). YouCook [Dataset]. https://opendatalab.com/OpenDataLab/YouCook
    Explore at:
    zip(1865855952 bytes)Available download formats
    Dataset updated
    Mar 22, 2023
    Dataset provided by
    State University of New York
    Description

    This data set was prepared from 88 open-source YouTube cooking videos. The YouCook dataset contains videos of people cooking various recipes. The videos were downloaded from YouTube and are all in the third-person viewpoint; they represent a significantly more challenging visual problem than existing cooking and kitchen datasets (the background kitchen/scene is different for many and most videos have dynamic camera changes). In addition, frame-by-frame object and action annotations are provided for training data (as well as a number of precomputed low-level features). Finally, each video has a number of human provided natural language descriptions (on average, there are eight different descriptions per video). This dataset has been created to serve as a benchmark in describing complex real-world videos with natural language descriptions.

  6. Johnny Depp Verdict victory

    • kaggle.com
    Updated Jun 7, 2022
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    Muhammad Ammar Jamshed (2022). Johnny Depp Verdict victory [Dataset]. https://www.kaggle.com/datasets/muhammadammarjamshed/johnny-depp-verdict-victory
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 7, 2022
    Dataset provided by
    Kaggle
    Authors
    Muhammad Ammar Jamshed
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    It's a video download from youtube, It shows the celebration outside of court in response to the verdict being in Depps Favour.

    I used it to experiment with a python image algorithm

  7. Indian Languages Audio Dataset

    • kaggle.com
    Updated Nov 3, 2023
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    HARSHMAN SOLANKI (2023). Indian Languages Audio Dataset [Dataset]. https://www.kaggle.com/datasets/hmsolanki/indian-languages-audio-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 3, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    HARSHMAN SOLANKI
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    India
    Description

    Description: The "Indian Languages Audio Dataset" is a collection of audio samples featuring a diverse set of 10 Indian languages. Each audio sample in this dataset is precisely 5 seconds in duration and is provided in MP3 format. It is important to note that this dataset is a subset of a larger collection known as the "Audio Dataset with 10 Indian Languages." The source of these audio samples is regional videos freely available on YouTube, and none of the audio samples or source videos are owned by the dataset creator.

    Languages Included: 1. Bengali 2. Gujarati 3. Hindi 4. Kannada 5. Malayalam 6. Marathi 7. Punjabi 8. Tamil 9. Telugu 10. Urdu

    This dataset offers a valuable resource for researchers, linguists, and machine learning enthusiasts who are interested in studying and analyzing the phonetics, accents, and linguistic characteristics of the Indian subcontinent. It is a representative sample of the linguistic diversity present in India, encompassing a wide array of languages and dialects. Researchers and developers are encouraged to explore this dataset to build applications or conduct research related to speech recognition, language identification, and other audio processing tasks.

    Additionally, the dataset is not limited to these 10 languages and has the potential for expansion. Given the dynamic nature of language use in India, this dataset can serve as a foundation for future data collection efforts involving additional Indian languages and dialects.

    Access to the "Indian Multilingual Audio Dataset - 10 Languages" is provided with the understanding that users will comply with applicable copyright and licensing restrictions. If users plan to extend this dataset or use it for commercial purposes, it is essential to seek proper permissions and adhere to relevant copyright and licensing regulations.

    By utilizing this dataset responsibly and ethically, users can contribute to the advancement of language technology and research, ultimately benefiting language preservation, speech recognition, and cross-cultural communication.

  8. R

    Accident Detection Model Dataset

    • universe.roboflow.com
    zip
    Updated Apr 8, 2024
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    Accident detection model (2024). Accident Detection Model Dataset [Dataset]. https://universe.roboflow.com/accident-detection-model/accident-detection-model/model/1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Apr 8, 2024
    Dataset authored and provided by
    Accident detection model
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Accident Bounding Boxes
    Description

    Accident-Detection-Model

    Accident Detection Model is made using YOLOv8, Google Collab, Python, Roboflow, Deep Learning, OpenCV, Machine Learning, Artificial Intelligence. It can detect an accident on any accident by live camera, image or video provided. This model is trained on a dataset of 3200+ images, These images were annotated on roboflow.

    Problem Statement

    • Road accidents are a major problem in India, with thousands of people losing their lives and many more suffering serious injuries every year.
    • According to the Ministry of Road Transport and Highways, India witnessed around 4.5 lakh road accidents in 2019, which resulted in the deaths of more than 1.5 lakh people.
    • The age range that is most severely hit by road accidents is 18 to 45 years old, which accounts for almost 67 percent of all accidental deaths.

    Accidents survey

    https://user-images.githubusercontent.com/78155393/233774342-287492bb-26c1-4acf-bc2c-9462e97a03ca.png" alt="Survey">

    Literature Survey

    • Sreyan Ghosh in Mar-2019, The goal is to develop a system using deep learning convolutional neural network that has been trained to identify video frames as accident or non-accident.
    • Deeksha Gour Sep-2019, uses computer vision technology, neural networks, deep learning, and various approaches and algorithms to detect objects.

    Research Gap

    • Lack of real-world data - We trained model for more then 3200 images.
    • Large interpretability time and space needed - Using google collab to reduce interpretability time and space required.
    • Outdated Versions of previous works - We aer using Latest version of Yolo v8.

    Proposed methodology

    • We are using Yolov8 to train our custom dataset which has been 3200+ images, collected from different platforms.
    • This model after training with 25 iterations and is ready to detect an accident with a significant probability.

    Model Set-up

    Preparing Custom dataset

    • We have collected 1200+ images from different sources like YouTube, Google images, Kaggle.com etc.
    • Then we annotated all of them individually on a tool called roboflow.
    • During Annotation we marked the images with no accident as NULL and we drew a box on the site of accident on the images having an accident
    • Then we divided the data set into train, val, test in the ratio of 8:1:1
    • At the final step we downloaded the dataset in yolov8 format.
      #### Using Google Collab
    • We are using google colaboratory to code this model because google collab uses gpu which is faster than local environments.
    • You can use Jupyter notebooks, which let you blend code, text, and visualisations in a single document, to write and run Python code using Google Colab.
    • Users can run individual code cells in Jupyter Notebooks and quickly view the results, which is helpful for experimenting and debugging. Additionally, they enable the development of visualisations that make use of well-known frameworks like Matplotlib, Seaborn, and Plotly.
    • In Google collab, First of all we Changed runtime from TPU to GPU.
    • We cross checked it by running command ‘!nvidia-smi’
      #### Coding
    • First of all, We installed Yolov8 by the command ‘!pip install ultralytics==8.0.20’
    • Further we checked about Yolov8 by the command ‘from ultralytics import YOLO from IPython.display import display, Image’
    • Then we connected and mounted our google drive account by the code ‘from google.colab import drive drive.mount('/content/drive')’
    • Then we ran our main command to run the training process ‘%cd /content/drive/MyDrive/Accident Detection model !yolo task=detect mode=train model=yolov8s.pt data= data.yaml epochs=1 imgsz=640 plots=True’
    • After the training we ran command to test and validate our model ‘!yolo task=detect mode=val model=runs/detect/train/weights/best.pt data=data.yaml’ ‘!yolo task=detect mode=predict model=runs/detect/train/weights/best.pt conf=0.25 source=data/test/images’
    • Further to get result from any video or image we ran this command ‘!yolo task=detect mode=predict model=runs/detect/train/weights/best.pt source="/content/drive/MyDrive/Accident-Detection-model/data/testing1.jpg/mp4"’
    • The results are stored in the runs/detect/predict folder.
      Hence our model is trained, validated and tested to be able to detect accidents on any video or image.

    Challenges I ran into

    I majorly ran into 3 problems while making this model

    • I got difficulty while saving the results in a folder, as yolov8 is latest version so it is still underdevelopment. so i then read some blogs, referred to stackoverflow then i got to know that we need to writ an extra command in new v8 that ''save=true'' This made me save my results in a folder.
    • I was facing problem on cvat website because i was not sure what
  9. Physical Exercise Recognition|Time Series Dataset

    • kaggle.com
    Updated Feb 22, 2023
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    Muhannad Tuameh (2023). Physical Exercise Recognition|Time Series Dataset [Dataset]. https://www.kaggle.com/datasets/muhannadtuameh/exercise-recognition-time-series/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 22, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Muhannad Tuameh
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Content

    This dataset represents sequential poses that can be used to distinguish 5 physical exercises. The exercises are Push-up, Pull-up, Sit-up, Jumping Jack and Squat. The dataset consists of 33 landmarks that represents several important body parts' positions. Using these landmarks, the angles and the distances between several landmarks are calculated and included in the dataset. The sequence of the poses is provided by preserving the frame order in every record.

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F5365924%2Fb8c7ec50ebc270533628c7d05966ecbd%2FScreenshot%202023-02-22%20at%2020.30.37.png?generation=1677087060116097&alt=media" alt="">

    Collection Process

    About 500 videos of people doing the exercises have been used in order to collect this data. The videos are from Countix Dataset that contain the YouTube links of several human activity videos. Using a simple Python script, the videos of 5 different physical exercises are downloaded. All the frames of the videos are extracted, processed and included in the dataset.

    Processing Data

    For every frame, MediaPipe framework is used for applying pose estimation, which detects the human skeleton of the person in the frame. The landmark model in MediaPipe Pose predicts the location of 33 pose landmarks (see figure below). Visit Mediapipe Pose Classification page for more details. Using these landmarks, the angles and the distances between several landmarks are calculated.

    https://mediapipe.dev/images/mobile/pose_tracking_full_body_landmarks.png" alt="33 pose landmarks">

  10. Google Data Analytics Capstone Project

    • kaggle.com
    Updated Oct 1, 2022
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    Data Rookie (2022). Google Data Analytics Capstone Project [Dataset]. https://www.kaggle.com/datasets/rookieaj1234/google-data-analytics-capstone-project
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 1, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Data Rookie
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Project Name: Divvy Bikeshare Trip Data_Year2020 Date Range: April 2020 to December 2020. Analyst: Ajith Software: R Program, Microsoft Excel IDE: RStudio

    The following are the basic system requirements, necessary for the project: Processor: Intel i3 or AMD Ryzen 3 and higher Internal RAM: 8 GB or higher Operating System: Windows 7 or above, MacOS

    **Data Usage License: https://ride.divvybikes.com/data-license-agreement ** Introduction:

    In this case, study we aim to utilize different data analysis techniques and tools, to understand the rental patterns of the divvy bike sharing company and understand the key business improvement suggestions. This case study is a mandatory project to be submitted to achieve the Google Data Analytics Certification. The data utilized in this case study was licensed based on the provided data usage license. The trips between April 2020 to December 2020 are used to analyse the data.

    Scenario: Marketing team needs to design marketing strategies aimed at converting casual riders into annual members. In order to do that, however, the marketing analyst team needs to better understand how annual members and casual riders differ.

    Objective: The main objective of this case study, is to understand the customer usage patterns and the breakdown of customers, based on their subscription status and the average durations of the rental bike usage.

    Introduction to Data: The Data provided for this project, is adhered to the data usage license, laid down by the source company. The source data was provided in the CSV files and are month and quarter breakdowns. A total of 13 columns of data was provided in each csv file.

    The following are the columns, which were initially observed across the datasets.

    Ride_id Ride_type Start_station_name Start_station_id End_station_name End_station_id Usertype Start_time End_time Start_lat Start_lng End_lat End_lng

    Documentation, Cleaning and Preparing Data for Analysis: The total size of the datasets, for the year 2020, is approximately 450 MB, which is tiring job, when you have to upload them to the SQL database and visualize using the BI tools. I wanted to improve my skills into R environment and this is the best opportunity and optimal to use R for the data analysis.

    For more insights, installation procedures for R and RStudio, please refer to the following URL, for additional information.

    R Projects Document: https://www.r-project.org/other-docs.html RStudio Download: https://www.rstudio.com/products/rstudio/ Installation Guide: https://www.youtube.com/watch?v=TFGYlKvQEQ4

  11. Number of global social network users 2017-2028

    • statista.com
    • es.statista.com
    • +1more
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    Stacy Jo Dixon, Number of global social network users 2017-2028 [Dataset]. https://www.statista.com/topics/1164/social-networks/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    How many people use social media?

                  Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.
    
                  Who uses social media?
                  Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
                  when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.
    
                  How much time do people spend on social media?
                  Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.
    
                  What are the most popular social media platforms?
                  Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.
    
  12. TikTok global quarterly downloads 2018-2024

    • statista.com
    • es.statista.com
    • +1more
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    Statista Research Department, TikTok global quarterly downloads 2018-2024 [Dataset]. https://www.statista.com/topics/1164/social-networks/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    In the fourth quarter of 2024, TikTok generated around 186 million downloads from users worldwide. Initially launched in China first by ByteDance as Douyin, the short-video format was popularized by TikTok and took over the global social media environment in 2020. In the first quarter of 2020, TikTok downloads peaked at over 313.5 million worldwide, up by 62.3 percent compared to the first quarter of 2019.

                  TikTok interactions: is there a magic formula for content success?
    
                  In 2024, TikTok registered an engagement rate of approximately 4.64 percent on video content hosted on its platform. During the same examined year, the social video app recorded over 1,100 interactions on average. These interactions were primarily composed of likes, while only recording less than 20 comments per piece of content on average in 2024.
                  The platform has been actively monitoring the issue of fake interactions, as it removed around 236 million fake likes during the first quarter of 2024. Though there is no secret formula to get the maximum of these metrics, recommended video length can possibly contribute to the success of content on TikTok.
                  It was recommended that tiny TikTok accounts with up to 500 followers post videos that are around 2.6 minutes long as of the first quarter of 2024. While, the ideal video duration for huge TikTok accounts with over 50,000 followers was 7.28 minutes. The average length of TikTok videos posted by the creators in 2024 was around 43 seconds.
    
                  What’s trending on TikTok Shop?
    
                  Since its launch in September 2023, TikTok Shop has become one of the most popular online shopping platforms, offering consumers a wide variety of products. In 2023, TikTok shops featuring beauty and personal care items sold over 370 million products worldwide.
                  TikTok shops featuring womenswear and underwear, as well as food and beverages, followed with 285 and 138 million products sold, respectively. Similarly, in the United States market, health and beauty products were the most-selling items,
                  accounting for 85 percent of sales made via the TikTok Shop feature during the first month of its launch. In 2023, Indonesia was the market with the largest number of TikTok Shops, hosting over 20 percent of all TikTok Shops. Thailand and Vietnam followed with 18.29 and 17.54 percent of the total shops listed on the famous short video platform, respectively.
    
  13. Most liked TikTok videos of all time 2023

    • statista.com
    • es.statista.com
    • +1more
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    Statista Research Department, Most liked TikTok videos of all time 2023 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    With barely 10 seconds and 61 million likes, Bella Poach's lip syncing "M to the B" by Millie B was the most engaging video on TikTok as of March 2023. Bella Poarch, who as of the beginning of 2023 was the third-most followed creator on the popular social video platform, rose to popularity as a singer and content creators since opening a TikTok account in January 2020. Second ranked "dancing in front of the bathroom mirror," by user @jamie32bsh generated almost 52 million likes between its upload time - January 2022 and March 2023.

  14. Reddit: global paid subscription revenues 2018-2026

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    Statista Research Department, Reddit: global paid subscription revenues 2018-2026 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    In 2023, it was estimated that social forum and news aggregator Reddit saw over 26.5 million U.S. dollars in revenues from global paying users with an annual subscription. A premium Reddit subscription comes with an ad-free environment, as well as the possibility to join premium subreddits such as r/lounge. In 2022, Reddit counted approximately 530 thousand paying users. By 2026, Reddit annual subscription revenues are estimated to bring in 36.5 million U.S. dollars in revenues.

  15. U.S. Facebook data requests from government agencies 2013-2023

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    Stacy Jo Dixon, U.S. Facebook data requests from government agencies 2013-2023 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    Facebook received 73,390 user data requests from federal agencies and courts in the United States during the second half of 2023. The social network produced some user data in 88.84 percent of requests from U.S. federal authorities. The United States accounts for the largest share of Facebook user data requests worldwide.

  16. Facebook users worldwide 2017-2027

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    Stacy Jo Dixon, Facebook users worldwide 2017-2027 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, 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 and count multiple accounts by persons only once.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).

  17. Countries with the most Facebook users 2024

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    Stacy Jo Dixon, Countries with the most Facebook users 2024 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    Which county has the most Facebook users?

                  There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.
    
                  Facebook – the most used social media
    
                  Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.
    
                  Facebook usage by device
                  As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.
    
  18. Average daily time spent on social media worldwide 2012-2024

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    Stacy Jo Dixon, Average daily time spent on social media worldwide 2012-2024 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    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.
    
  19. TikTok: account removed 2020-2024, by reason

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    Statista Research Department, TikTok: account removed 2020-2024, by reason [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    During the fourth quarter 2024, approximately 20.6 million TikTok accounts were removed from the platform due to suspicion of being operated by users under the age of 13. During the last measured period, around 185 million fake accounts were removed from fake accounts removed from TikTok.

  20. Instagram: distribution of global audiences 2024, by gender

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    Stacy Jo Dixon, Instagram: distribution of global audiences 2024, by gender [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

                  Instagram’s Global Audience
    
                  As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
                  As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.
    
                  Who is winning over the generations?
    
                  Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.
    
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Statista (2025). YouTube users worldwide 2020-2029 [Dataset]. https://www.statista.com/forecasts/1144088/youtube-users-in-the-world
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YouTube users worldwide 2020-2029

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56 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 7, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
YouTube, Worldwide
Description

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.

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