At MFour, our Behavioral Data stands out for its uniqueness and depth of insights. What makes our data genuinely exceptional is the combination of several key factors:

• First-Party Opt-In Data: Our data is sourced directly from our opt-in panel of consumers who willingly participate in research and provide observed behaviors. This ensures the highest data quality and eliminates privacy concerns. CCPA compliant.

• Unparalleled Data Coverage: With access to 3B+ billion events, we have an extensive pool of participants who allow us to observe their brick + mortar location visitation, app + web smartphone usage, or both. This large-scale coverage provides robust and reliable insights.

• Our data is generally sourced through our Surveys On The Go (SOTG) mobile research app, where consumers are incentivized with cash rewards to participate in surveys and share their observed behaviors. This incentivized approach ensures a willing and engaged panel, leading to the highest-quality data.

The primary use cases and verticals of our Behavioral Data Product are diverse and varied. Some key applications include:

• Data Acquisition and Modeling: Our data helps businesses acquire valuable insights into consumer behavior and enables modeling for various research objectives.

• Shopper Data Analysis: By understanding purchase behavior and patterns, businesses can optimize their strategies, improve targeting, and enhance customer experiences.

• Media Consumption Insights: Our data provides a deep understanding of viewer behavior and patterns across popular platforms like YouTube, Amazon Prime, Netflix, and Disney+, enabling effective media planning and content optimization.

• App Performance Optimization: Analyzing app behavior allows businesses to monitor usage patterns, track key performance indicators (KPIs), and optimize app experiences to drive user engagement and retention.

• Location-Based Targeting: With our detailed location data, businesses can map out consumer visits to physical venues and combine them with web and app behavior to create predictive ad targeting strategies.

• Audience Creation for Ad Placement: Our data enables the creation of highly targeted audiences for ad campaigns, ensuring better reach and engagement with relevant consumer segments.

The Behavioral Data Product complements our comprehensive suite of data solutions in the broader context of our data offering. It provides granular and event-level insights into consumer behaviors, which can be combined with other data sets such as survey responses, demographics, or custom profiling questions to offer a holistic understanding of consumer preferences, motivations, and actions.

MFour's Behavioral Data empowers businesses with unparalleled consumer insights, allowing them to make data-driven decisions, uncover new opportunities, and stay ahead in today's dynamic market landscape.

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.

Concise comparison of the top 10 YouTube alternatives for content creators in 2025. Covers monetization, audience size, and ideal use cases.

Context

The data presented here was collected in a network section from Universidad Del Cauca, Popayán, Colombia by performing packet captures at different hours, during morning and afternoon, over six days (April 26, 27, 28 and May 9, 11 and 15) of 2017. A total of 3.577.296 instances were collected and are currently stored in a CSV (Comma Separated Values) file.

Content

This dataset contains 87 features. Each instance holds the information of an IP flow generated by a network device i.e., source and destination IP addresses, ports, interarrival times, layer 7 protocol (application) used on that flow as the class, among others. Most of the attributes are numeric type but there are also nominal types and a date type due to the Timestamp.

The flow statistics (IP addresses, ports, inter-arrival times, etc) were obtained using CICFlowmeter (http://www.unb.ca/cic/research/applications.html - https://github.com/ISCX/CICFlowMeter). The application layer protocol was obtained by performing a DPI (Deep Packet Inspection) processing on the flows with ntopng (https://www.ntop.org/products/traffic-analysis/ntop/ - https://github.com/ntop/ntopng).

For further information and if you find this dataset useful, please read and cite the following papers:

Research Gate: https://www.researchgate.net/publication/326150046_Personalized_Service_Degradation_Policies_on_OTT_Applications_Based_on_the_Consumption_Behavior_of_Users

Research Gate: https://www.researchgate.net/publication/335954240_Consumption_Behavior_Analysis_of_Over_The_Top_Services_Incremental_Learning_or_Traditional_Methods

Springer: https://link.springer.com/chapter/10.1007/978-3-319-95168-3_37

IEEExplore https://ieeexplore.ieee.org/document/8845576

Research Gate: https://www.researchgate.net/publication/345990587_Smart_User_Consumption_Profiling_Incremental_Learning-based_OTT_Service_Degradation

IEEExpore https://ieeexplore.ieee.org/document/9258898

Acknowledgements

I would like to thank Universidad Del Cauca for supporting the research that generated this dataset and Colciencias for my PhD scholarship.

Inspiration

Considering that most of the network traffic classification datasets are aimed only at identifying the type of application an IP flow holds (WWW, DNS, FTP, P2P, Telnet,etc), this dataset goes a step further by generating machine learning models capable of detecting specific applications such as Facebook, YouTube, Instagram, etc, from IP flow statistics (currently 75 applications).

We provide text metadata, image frames, and thumbnails of YouTube videos classified as harmful or harmless by domain experts, GPT-4-Turbo, and crowdworkers. Harmful videos are categorized into one or more of six harm categories: Information harms (IH), Hate and Harassment harms (HH), Clickbait harms (CB), Addictive harms (ADD), Sexual harms (SXL), and Physical harms (PH).

This repository includes the text metadata and a link to external cloud storage for the image data.

Text Metadata

Folder Subfolder

Videos

Ground Truth Harmful_full_agreement(classified as harmful by all the three actors) 5,109

Harmful_subset_agreement(classified as harmful by more than two actors) 14,019

Domain Experts Harmful 15,115

Harmless 3,303

GPT-4-Turbo Harmful 10,495

Harmless 7,818

Crowdworkers (Workers from Amazon Mechanical Turk) Harmful 12,668

Harmless 4,390

Unannotated large pool

60,906

Note. The term "actor" refers to the annotating entities: domain experts, GPT-4-Turbo, and crowdworkers

Explanations about the indicators

1. Ground truth - harmful_full_agreement & harmful_subset agreement

• links

• video_id

• channel

• description

• transcript

• date

• maj_harmcat: In the full_agreement version, this represents a harm category identified by all three actors. In the subset_agreement version, it represents a harm category classified by more than two actors.

• all_harmcat: This includes all harm categories classified by any of the actors without requiring agreement. It captures all classified categories.

1. Domain Experts, GPT-4-Turbo, Crowdworkers

• links

• video_id

• channel

• description

• transcript

• date

• harmcat

1. Unannotated large pool

• links

• video_id

• channel

• description

• transcript

• date

Note. Some data from the external dataset does not include date information. In such cases, the date was marked as 1990-01-01.We retrieved transcripts using the YouTubeTranscriptApi. If a video does not have any text data in the transcript section, it means the API failed to retrieve the transcript, possibly because the video does not contain any detectable language.

Some image frames are also available in the pickle file.

Image data

The image frames and thumbnails are available at this link: https://ucdavis.app.box.com/folder/302772803692?s=d23b20snl1slwkuh4pgvjs31m7r1xae2

1. Image frames (imageframes_1-20.zip): Image frames are organized into 20 zip folders due to the large size of the image frames. Each zip folder contains subfolders named after the unique video IDs of the annotated videos. Inside each subfolder, there are 15 sequentially numbered image frames (from 0 to 14) extracted from the corresponding video. The image frame folders do not distinguish between videos classified as harmful or non-harmful.

2. Thumbnails (Thumbnails.zip): The zip folder contains thumbnails from the individual videos used in classification. Each thumbnail is named using the unique video ID. This folder does not distinguish between videos classified as harmful or harmless

Related works (in preprint)

For details about the harm classification taxonomy and the performance comparison between crowdworkers, GPT-4-Turbo, and domain experts, please see https://arxiv.org/abs/2411.05854.

As of January 2024, #love was the most used hashtag on Instagram, being included in over two billion posts on the social media platform. #Instagood and #instagram were used over one billion times as of early 2024.

The dataset is a set of network traffic traces in pcap/csv format captured from a single user. The traffic is classified in 5 different activities (Video, Bulk, Idle, Web, and Interactive) and the label is shown in the filename. There is also a file (mapping.csv) with the mapping of the host's IP address, the csv/pcap filename and the activity label.

Activities:

Interactive: applications that perform real-time interactions in order to provide a suitable user experience, such as editing a file in google docs and remote CLI's sessions by SSH. Bulk data transfer: applications that perform a transfer of large data volume files over the network. Some examples are SCP/FTP applications and direct downloads of large files from web servers like Mediafire, Dropbox or the university repository among others. Web browsing: contains all the generated traffic while searching and consuming different web pages. Examples of those pages are several blogs and new sites and the moodle of the university. Vídeo playback: contains traffic from applications that consume video in streaming or pseudo-streaming. The most known server used are Twitch and Youtube but the university online classroom has also been used. Idle behaviour: is composed by the background traffic generated by the user computer when the user is idle. This traffic has been captured with every application closed and with some opened pages like google docs, YouTube and several web pages, but always without user interaction.

The capture is performed in a network probe, attached to the router that forwards the user network traffic, using a SPAN port. The traffic is stored in pcap format with all the packet payload. In the csv file, every non TCP/UDP packet is filtered out, as well as every packet with no payload. The fields in the csv files are the following (one line per packet): Timestamp, protocol, payload size, IP address source and destination, UDP/TCP port source and destination. The fields are also included as a header in every csv file.

The amount of data is stated as follows:

Bulk : 19 traces, 3599 s of total duration, 8704 MBytes of pcap files Video : 23 traces, 4496 s, 1405 MBytes Web : 23 traces, 4203 s, 148 MBytes Interactive : 42 traces, 8934 s, 30.5 MBytes Idle : 52 traces, 6341 s, 0.69 MBytes

The code of our machine learning approach is also included. There is a README.txt file with the documentation of how to use the code.

RTB Maps is a cloud-based electronic Atlas. We used ArGIS 10 for Desktop with Spatial Analysis Extension, ArcGIS 10 for Server on-premise, ArcGIS API for Javascript, IIS web services based on .NET, and ArcGIS Online combining data on the cloud with data and applications on our local server to develop an Atlas that brings together many of the map themes related to development of roots, tubers and banana crops. The Atlas is structured to allow our participating scientists to understand the distribution of the crops and observe the spatial distribution of many of the obstacles to production of these crops. The Atlas also includes an application to allow our partners to evaluate the importance of different factors when setting priorities for research and development. The application uses weighted overlay analysis within a multi-criteria decision analysis framework to rate the importance of factors when establishing geographic priorities for research and development.Datasets of crop distribution maps, agroecology maps, biotic and abiotic constraints to crop production, poverty maps and other demographic indicators are used as a key inputs to multi-objective criteria analysis.Further metadata/references can be found here: http://gisweb.ciat.cgiar.org/RTBmaps/DataAvailability_RTBMaps.htmlDISCLAIMER, ACKNOWLEDGMENTS AND PERMISSIONS:This service is provided by Roots, Tubers and Bananas CGIAR Research Program as a public service. Use of this service to retrieve information constitutes your awareness and agreement to the following conditions of use.This online resource displays GIS data and query tools subject to continuous updates and adjustments. The GIS data has been taken from various, mostly public, sources and is supplied in good faith.RTBMaps GIS Data Disclaimer• The data used to show the Base Maps is supplied by ESRI.• The data used to show the photos over the map is supplied by Flickr.• The data used to show the videos over the map is supplied by Youtube.• The population map is supplied to us by CIESIN, Columbia University and CIAT.• The Accessibility map is provided by Global Environment Monitoring Unit - Joint Research Centre of the European Commission. Accessibility maps are made for a specific purpose and they cannot be used as a generic dataset to represent "the accessibility" for a given study area.• Harvested area and yield for banana, cassava, potato, sweet potato and yam for the year 200, is provided by EarthSat (University of Minnesota’s Institute on the Environment-Global Landscapes initiative and McGill University’s Land Use and the Global Environment lab). Dataset from Monfreda C., Ramankutty N., and Foley J.A. 2008.• Agroecology dataset: global edapho-climatic zones for cassava based on mean growing season, temperature, number of dry season months, daily temperature range and seasonality. Dataset from CIAT (Carter et al. 1992)• Demography indicators: Total and Rural Population from Center for International Earth Science Information Network (CIESIN) and CIAT 2004.• The FGGD prevalence of stunting map is a global raster datalayer with a resolution of 5 arc-minutes. The percentage of stunted children under five years old is reported according to the lowest available sub-national administrative units: all pixels within the unit boundaries will have the same value. Data have been compiled by FAO from different sources: Demographic and Health Surveys (DHS), UNICEF MICS, WHO Global Database on Child Growth and Malnutrition, and national surveys. Data provided by FAO – GIS Unit 2007.• Poverty dataset: Global poverty headcount and absolute number of poor. Number of people living on less than $1.25 or $2.00 per day. Dataset from IFPRI and CIATTHE RTBMAPS GROUP MAKES NO WARRANTIES OR GUARANTEES, EITHER EXPRESSED OR IMPLIED AS TO THE COMPLETENESS, ACCURACY, OR CORRECTNESS OF THE DATA PORTRAYED IN THIS PRODUCT NOR ACCEPTS ANY LIABILITY, ARISING FROM ANY INCORRECT, INCOMPLETE OR MISLEADING INFORMATION CONTAINED THEREIN. ALL INFORMATION, DATA AND DATABASES ARE PROVIDED "AS IS" WITH NO WARRANTY, EXPRESSED OR IMPLIED, INCLUDING BUT NOT LIMITED TO, FITNESS FOR A PARTICULAR PURPOSE. By accessing this website and/or data contained within the databases, you hereby release the RTB group and CGCenters, its employees, agents, contractors, sponsors and suppliers from any and all responsibility and liability associated with its use. In no event shall the RTB Group or its officers or employees be liable for any damages arising in any way out of the use of the website, or use of the information contained in the databases herein including, but not limited to the RTBMaps online Atlas product.APPLICATION DEVELOPMENT:• Desktop and web development - Ernesto Giron E. (GeoSpatial Consultant) e.giron.e@gmail.com• GIS Analyst - Elizabeth Barona. (Independent Consultant) barona.elizabeth@gmail.comCollaborators:Glenn Hyman, Bernardo Creamer, Jesus David Hoyos, Diana Carolina Giraldo Soroush Parsa, Jagath Shanthalal, Herlin Rodolfo Espinosa, Carlos Navarro, Jorge Cardona and Beatriz Vanessa Herrera at CIAT, Tunrayo Alabi and Joseph Rusike from IITA, Guy Hareau, Reinhard Simon, Henry Juarez, Ulrich Kleinwechter, Greg Forbes, Adam Sparks from CIP, and David Brown and Charles Staver from Bioversity International.Please note these services may be unavailable at times due to maintenance work.Please feel free to contact us with any questions or problems you may be having with RTBMaps.

ASLNow!

ASLNow! is a web app designed to make learning ASL fingerspelling easy and fun! You can try it live at asl-now.vercel.app. Demo: https://www.youtube.com/watch?v=Wi5tAxVasq8

  Dataset

This dataset, used to train the fingerspelling model is licensed under the MIT License. It will be updated frequently as more data is collected. The dataset is collected from multiple participants told to sign ASL letters into a camera and detecting hand landmarks using the Mediapipe… See the full description on the dataset page: https://huggingface.co/datasets/sid220/asl-now-fingerspelling.

Use of social media and online-based applications in the context of scientific activities at German universities and research institutions. Topics: assessment of activities and scope of scientific activities; professional and private use of online tools and social media; frequency of occupational use of online tools and social media; active and passive use of selected Web 2.0 applications; use of online tools and social media in various scientific fields of activity (research, teaching, administration, communication) and deepening activities within the field of research; attitudes of scientists towards the Internet and social media; recognition and dissemination of virtual research environments; online access media; inquired tools and applications: Social networks (Facebook, Google+), scientific / professional networks (Xing, Academia.edu), videoconference/VoIP (Skype, Adobe Connect), microblogs (Twitter), weblogs, wikipedia, other wikis (company Wiki, technical Wikis, etc.), content sharing / cloud services (dropbox, slideshare), online text editors (EtherPad, Google Docs), internet forums, mailing lists, chat / instant messaging (Skype, ICQ), online archiv/data bases (German digital library, Arxiv.org), social bookmarking services (Delicious, Bibsonomy), literature management (Mendeley, Zotero), video / photo community portals (YouTube, Flickr), learning management systems; termination tools and coordination tools (Assana, Foodle, Trello). Demography: age (year of birth and categories); sex; highest academic degree; function at the university / research institution; departmental affiliation; University affiliation; duration of previous scientific activity; percentage of scientific activity by activity. Nutzung von Social Media und onlinebasierten Anwendungen im Rahmen wissenschaftlicher Tätigkeit an deutschen Hochschulen und Forschungseinrichtungen. Themen: Berufliche und private Nutzung von Online-Werkzeugen und Social Media; Häufigkeit der beruflichen Nutzung von Online-Werkzeugen und Social Media; aktive und passive Nutzung ausgewählter Web 2.0-Anwendungen; Einsatz von Online-Werkzeugen und Social Media in verschiedenen wissenschaftlichen Tätigkeitsfeldern (Forschung, Lehre, Administration, Kommunikation) und vertiefend Aktivitäten innerhalb des Tätigkeitsbereiches Forschung; Einstellungen gegenüber Internet und Social Media; Bekanntheit und Verbreitung von Virtuellen Forschungsumgebungen; Online-Zugriffsmedien; erfragte Werkzeuge und Anwendungen: Soziale Netzwerke (Facebook, Google+), Wissenschaftliche/Berufliche Netzwerke (Xing, Academia.edu), Videokonferenz/VoIP (Skype, Adobe Connect), Mikroblogs (Twitter), Weblogs, Wikipedia, andere Wikis (Firmenwiki, fachspezifische Wikis etc.), Content Sharing/Cloud-Dienste (Dropbox, Slideshare), Online-Texteditoren (EtherPad, Google Docs), Internetforen, Mailinglisten, Chat/Instant Messaging (Skype, ICQ), Online-Archive/Datenbanken (Deutsche Digitale Bibliothek, Arxiv.org), Social Bookmarking Services (Delicious, Bibsonomy), Literaturverwaltung (Mendeley, Zotero), Video/Foto Community-Portale (YouTube, Flickr), Lernmanagementsysteme, Terminierungs- und Koordinationswerkzeuge (Assana, Foodle, Trello). Demographie: Alter (Geburtsjahr und kategorisiert); Geschlecht; höchster akademischer Abschluss; Funktion, in der der Befragte an der Hochschule/Forschungseinrichtung tätig ist; Fachbereichszugehörigkeit; Fachgebiet innerhalb der Fächergruppe; Hochschulzugehörigkeit; Dauer der bisherigen wissenschaftlichen Tätigkeit; prozentuale Aufteilung der wissenschaftlichen Tätigkeit nach Tätigkeitsbereichen. Zusätzlich verkodet wurde: lfd. Nr; Gewichtungsfaktoren; Region (grob); Bundesland; Datensatz deutsch/ englisch; Skalen Privacy Concerns, Computer Anxiety, Computer Self Effiacy und Curiosity.

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.

Cristiano Ronaldo has one of the most popular Instagram accounts as of April 2024.

              The Portuguese footballer is the most-followed person on the photo sharing app platform with 628 million followers. Instagram's own account was ranked first with roughly 672 million followers.

              How popular is Instagram?

              Instagram is a photo-sharing social networking service that enables users to take pictures and edit them with filters. The platform allows users to post and share their images online and directly with their friends and followers on the social network. The cross-platform app reached one billion monthly active users in mid-2018. In 2020, there were over 114 million Instagram users in the United States and experts project this figure to surpass 127 million users in 2023.

              Who uses Instagram?

              Instagram audiences are predominantly young – recent data states that almost 60 percent of U.S. Instagram users are aged 34 years or younger. Fall 2020 data reveals that Instagram is also one of the most popular social media for teens and one of the social networks with the biggest reach among teens in the United States.

              Celebrity influencers on Instagram
              Many celebrities and athletes are brand spokespeople and generate additional income with social media advertising and sponsored content. Unsurprisingly, Ronaldo ranked first again, as the average media value of one of his Instagram posts was 985,441 U.S. dollars.

Here are a few use cases for this project:

1. Education Tools: The "SIGN LANGUAGE RECOGNITION" model can be used in educational platforms or apps designed for learning sign language. The model can provide real-time feedback on users' signing accuracy and help them improve their signing skills.

2. Communication Aid for the Hearing-Impaired: This model can be implemented in applications that assist hearing-impaired individuals in communicating with others who do not understand sign language. By converting signed gestures into written or spoken language, the system could facilitate more seamless communication.

3. Real-Time Sign Language Translator: Utilization of this tool can be done in video conferencing platforms to provide real-time translation of sign language, which can make online meetings, webinars, or classes accessible to those who use sign language.

4. Accessibility in Digital Media: It could be used in platforms like YouTube or streaming services to provide sign language translations for videos that don't already have them, thereby making content more accessible.

5. Interactive Entertainment: For game developers, the tool can be used to create interactive experiences or games that use sign language. This would not only provide a fun, immersive experience, but also promote sign language learning.

Instagram’s most popular post

              As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
              After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.

              Instagram’s most popular accounts

              As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.

              Instagram influencers

              In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.

              Instagram around the globe

              Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.

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.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

The number of Reddit users in the United States was forecast to continuously increase between 2024 and 2028 by in total 10.3 million users (+5.21 percent). After the ninth consecutive increasing year, the Reddit user base is estimated to reach 208.12 million users and therefore a new peak in 2028. Notably, the number of Reddit users of was continuously increasing over the past years.User figures, shown here with regards to the platform reddit, 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. Reddit users encompass both users that are logged in and those that are not.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 Reddit users in countries like Mexico and Canada.

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

This statistic shows a ranking of the estimated number of Youtube users in 2020 in Africa, differentiated by country. The user numbers 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 more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).