7 datasets found
  1. Average daily time spent on social media worldwide 2012-2024

    • statista.com
    • wwwexpressvpn.online
    • +1more
    Updated Apr 10, 2024
    + more versions
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    Statista (2024). Average daily time spent on social media worldwide 2012-2024 [Dataset]. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/
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    Dataset updated
    Apr 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    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.

  2. Z

    Keras video classification example with a subset of UCF101 - Action...

    • data.niaid.nih.gov
    • zenodo.org
    Updated May 11, 2023
    + more versions
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    Mikolaj Buchwald (2023). Keras video classification example with a subset of UCF101 - Action Recognition Data Set (top 10 videos) [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_7882860
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    Dataset updated
    May 11, 2023
    Dataset authored and provided by
    Mikolaj Buchwald
    License

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

    Description

    Classify video clips with natural scenes of actions performed by people visible in the videos.

    See the UCF101 Dataset web page: https://www.crcv.ucf.edu/data/UCF101.php#Results_on_UCF101

    This example datasets consists of the 10 most numerous video from the UCF101 dataset. For the top 5 version, see: https://doi.org/10.5281/zenodo.7924745 .

    Based on this code: https://keras.io/examples/vision/video_classification/ (needs to be updated, if has not yet been already; see the issue: https://github.com/keras-team/keras-io/issues/1342).

    Testing if data can be downloaded from figshare with wget, see: https://github.com/mojaveazure/angsd-wrapper/issues/10

    For generating the subset, see this notebook: https://colab.research.google.com/github/sayakpaul/Action-Recognition-in-TensorFlow/blob/main/Data_Preparation_UCF101.ipynb -- however, it also needs to be adjusted (if has not yet been already - then I will post a link to the notebook here or elsewhere, e.g., in the corrected notebook with Keras example).

    I would like to thank Sayak Paul for contacting me about his example at Keras documentation being out of date.

    Cite this dataset as:

    Soomro, K., Zamir, A. R., & Shah, M. (2012). UCF101: A dataset of 101 human actions classes from videos in the wild. arXiv preprint arXiv:1212.0402. https://doi.org/10.48550/arXiv.1212.0402

    To download the dataset via the command line, please use:

    wget -q https://zenodo.org/record/7882861/files/ucf101_top10.tar.gz -O ucf101_top10.tar.gz tar xf ucf101_top10.tar.gz

  3. YouTube users worldwide 2020-2029

    • statista.com
    Updated Mar 3, 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
    Mar 3, 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 232.5 million users (+24.91 percent). After the ninth consecutive increasing year, the Youtube user base is estimated to reach 1.2 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 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 Africa and South America.

  4. Wirestock's AI/ML Image Training Data, 4.5M Files with Metadata

    • datarade.ai
    .csv
    Updated Jul 18, 2023
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    WIRESTOCK (2023). Wirestock's AI/ML Image Training Data, 4.5M Files with Metadata [Dataset]. https://datarade.ai/data-products/wirestock-s-ai-ml-image-training-data-4-5m-files-with-metadata-wirestock
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    .csvAvailable download formats
    Dataset updated
    Jul 18, 2023
    Dataset provided by
    Wirestock
    Authors
    WIRESTOCK
    Area covered
    New Caledonia, Georgia, Chile, Estonia, Belarus, Jersey, Swaziland, Pakistan, Peru, Sudan
    Description

    Wirestock's AI/ML Image Training Data, 4.5M Files with Metadata: This data product is a unique offering in the realm of AI/ML training data. What sets it apart is the sheer volume and diversity of the dataset, which includes 4.5 million files spanning across 20 different categories. These categories range from Animals/Wildlife and The Arts to Technology and Transportation, providing a rich and varied dataset for AI/ML applications.

    The data is sourced from Wirestock's platform, where creators upload and sell their photos, videos, and AI art online. This means that the data is not only vast but also constantly updated, ensuring a fresh and relevant dataset for your AI/ML needs. The data is collected in a GDPR-compliant manner, ensuring the privacy and rights of the creators are respected.

    The primary use-cases for this data product are numerous. It is ideal for training machine learning models for image recognition, improving computer vision algorithms, and enhancing AI applications in various industries such as retail, healthcare, and transportation. The diversity of the dataset also means it can be used for more niche applications, such as training AI to recognize specific objects or scenes.

    This data product fits into Wirestock's broader data offering as a key resource for AI/ML training. Wirestock is a platform for creators to sell their work, and this dataset is a collection of that work. It represents the breadth and depth of content available on Wirestock, making it a valuable resource for any company working with AI/ML.

    The core benefits of this dataset are its volume, diversity, and quality. With 4.5 million files, it provides a vast resource for AI training. The diversity of the dataset, spanning 20 categories, ensures a wide range of images for training purposes. The quality of the images is also high, as they are sourced from creators selling their work on Wirestock.

    In terms of how the data is collected, creators upload their work to Wirestock, where it is then sold on various marketplaces. This means the data is sourced directly from creators, ensuring a diverse and unique dataset. The data includes both the images themselves and associated metadata, providing additional context for each image.

    The different image categories included in this dataset are Animals/Wildlife, The Arts, Backgrounds/Textures, Beauty/Fashion, Buildings/Landmarks, Business/Finance, Celebrities, Education, Emotions, Food Drinks, Holidays, Industrial, Interiors, Nature Parks/Outdoor, People, Religion, Science, Signs/Symbols, Sports/Recreation, Technology, Transportation, Vintage, Healthcare/Medical, Objects, and Miscellaneous. This wide range of categories ensures a diverse dataset that can cater to a variety of AI/ML applications.

  5. f

    Data from: S1 Dataset -

    • plos.figshare.com
    zip
    Updated Oct 5, 2023
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    Marco Faytong-Haro; Genesis Camacho-Leon; Roberto Páez-Plúas; Azza Sarfraz; Zouina Sarfraz; Jack Michel; Ivan Cherrez-Ojeda (2023). S1 Dataset - [Dataset]. http://doi.org/10.1371/journal.pone.0291709.s001
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    zipAvailable download formats
    Dataset updated
    Oct 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Marco Faytong-Haro; Genesis Camacho-Leon; Roberto Páez-Plúas; Azza Sarfraz; Zouina Sarfraz; Jack Michel; Ivan Cherrez-Ojeda
    License

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

    Description

    Background: Coronavirus disease (COVID-19) is a pandemic that has spread worldwide. Since its discovery, health measures have been put in place to help stop it from spreading. Proper education about COVID-19 is important because it helps people to follow health control measures and learn more about the disease. Objective: This study aimed to compare people´s knowledge of COVID-19 before and after a brief video-based educational intervention. Methods: 87 participants in Ecuador were recruited from a dataset of COVID-positive patients in Ecuador between December 2021 and February 2022. This was a cross-sectional, pre- and post-intervention study. First, COVID-19 knowledge was evaluated and then an educational intervention was provided as a video. After the intervention, the same knowledge questions were used to test the participants, and marginal homogeneity-based chi-square tests were employed for comparison. Results: After watching the educational video, participants knew more about the age group most likely to get the disease and their knowledge of how long it takes for Covid to spread. Their knowledge of other aspects of COVID-19 has also increased. Conclusion: This study shows that educational intervention positively affects the knowledge of people who watch it. At the end of the study, after the intervention, the study participants knew more than they had before. This could be a useful tool for identifying possible pandemics.

  6. YouTube users in India 2020-2029

    • statista.com
    Updated Mar 3, 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
    Mar 3, 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 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.

  7. Quarterly Netflix subscribers count worldwide 2013-2024

    • statista.com
    • flwrdeptvarieties.store
    Updated Mar 3, 2025
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    Statista (2025). Quarterly Netflix subscribers count worldwide 2013-2024 [Dataset]. https://www.statista.com/statistics/250934/quarterly-number-of-netflix-streaming-subscribers-worldwide/
    Explore at:
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Netflix's global subscriber base has reached an impressive milestone, surpassing 300 million paid subscribers worldwide in the fourth quarter of 2024. This marks a significant increase of nearly 20 million subscribers compared to the previous quarter, solidifying Netflix's position as a dominant force in the streaming industry. Adapting to customer losses Netflix's growth has not always been consistent. During the first half of 2022, the streaming giant lost over one million customers. In response to these losses, Netflix introduced an ad-supported tier in November of that same year. This strategic move has paid off, with the lower-cost plan attracting 70 million monthly active users globally by November 2024, demonstrating Netflix's ability to adapt to changing market conditions and consumer preferences. Global expansion Netflix continues to focus on international markets, with a forecast suggesting that the Asia Pacific region is expected to see the most substantial growth in the upcoming years, potentially reaching around 70.1 million subscribers by 2029. To correspond to the needs of the non-American target group, the company has heavily invested in international content in recent years, with Korean, Spanish, and Japanese being the most watched non-English content languages on the platform.

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    Learn how you can add new datasets to our index.

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Statista (2024). Average daily time spent on social media worldwide 2012-2024 [Dataset]. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/
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Average daily time spent on social media worldwide 2012-2024

Explore at:
Dataset updated
Apr 10, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
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.

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