This dataset provides a comprehensive overview of global internet usage as of 2024. It includes the number of internet users in each country, the percentage of the population with internet access, and the total internet traffic generated. This dataset can be used to analyze trends in internet adoption, digital inequality, and the potential impact of the internet on various sectors of the global economy.

Dataset Overview

This dataset provides a comprehensive overview of internet usage across countries as of 2024. It includes data on the percentage of the population using the internet, sourced from multiple organizations such as the World Bank (WB), International Telecommunication Union (ITU), and the CIA. The dataset covers all United Nations member states, excluding North Korea, and provides insights into internet penetration rates, user counts, and trends over recent years. The data is derived from household surveys and internet subscription statistics, offering a reliable snapshot of global digital connectivity.

Data Science Applications

This dataset can be used in various data science applications, including: - Digital Divide Analysis: Evaluate disparities in internet access between developed and developing nations. - Trend Analysis: Study the growth of internet penetration over time across different regions. - Policy Recommendations: Assist policymakers in identifying underserved areas and strategizing for improved connectivity. - Market Research: Help businesses identify potential markets for digital products or services. - Correlation Studies: Analyze relationships between internet penetration and socioeconomic indicators like GDP, education levels, or urbanization.

Column Descriptors

The dataset contains the following columns: 1. Location: Country or region name. 2. Rate (WB): Percentage of the population using the internet (World Bank data). 3. Year (WB): Year corresponding to the World Bank data. 4. Rate (ITU): Percentage of the population using the internet (ITU data). 5. Year (ITU): Year corresponding to the ITU data. 6. Users (CIA): Estimated number of internet users in absolute terms (CIA data). 7. Year (CIA): Year corresponding to the CIA data. 8. Notes: Additional notes or observations about specific entries.

Ethically Mined Data

The data has been sourced from publicly available and reputable organizations such as the World Bank, ITU, and CIA. These sources ensure transparency and ethical collection methods through household surveys and official statistics. The dataset excludes North Korea due to limited reliable information on its internet usage.

Acknowledgements

This dataset is based on information compiled from: - World Bank - International Telecommunication Union - CIA World Factbook - Wikipedia's "List of countries by number of Internet users" page

Special thanks to these organizations for providing open access to this valuable information, enabling deeper insights into global digital connectivity trends.

Citations: [1] https://en.wikipedia.org/wiki/List_of_countries_by_number_of_Internet_users [2] https://en.wikipedia.org/wiki/List_of_countries_by_number_of_Internet_users

This dataset contains country-level internet usage data from 2000 to 2023. It provides the percentage of the population using the internet in different countries over time. This data can be useful for analyzing global internet penetration, digital adoption trends, and technological growth across regions.

🔹 Dataset Information:

• Country Name & Code – Identifies each country.
• Yearly Internet Usage (%) – The percentage of the population using the internet from 2000 to 2023.
• Missing Values (No Data) – Some countries may have missing data for certain years.

📈 Potential Use Cases:

• Trend Analysis: Explore how internet usage has evolved globally.
• Regional Comparisons: Compare internet adoption across countries and continents.
• Machine Learning Applications
  • Time-Series Forecasting – Predict future internet usage trends using models like ARIMA, LSTM, or Prophet.
  • Clustering & Segmentation – Group countries based on their internet adoption rates using k-means or hierarchical clustering.
  • Feature Engineering – Use internet penetration as a predictor in socio-economic or technological development models.

📌 Source:

Modified from this source World bank group data

This dataset is valuable for data visualization, time-series analysis, and policy-making research related to digital growth.

Historical data of internet users per 100 people since 1954

Dataset

This dataset was created by Tanishq_102217227

Released under MIT

Contents

Internet in India began in 1986 and was available only to the educational and research community. General public access to the internet began on 15 August 1995, and as of 2020 there are 718.74 million active internet users that comprise 54.29% of the population.[1]

As of May 2014, the Internet is delivered to India mainly by 9 different undersea fibres, including SEA-ME-WE 3, Bay of Bengal Gateway and Europe India Gateway, arriving at 5 different landing points.[2] India also has one overland internet connection, at the city of Agartala near the border with Bangladesh.[3]

The Indian Government has embarked on projects such as BharatNet, Digital India, Brand India and Startup India to further expedite the growth of internet-based ecosystems.

Dataset

This dataset was created by VictorDaniloCastanedaPinzon

Contents

Table of INEBase Use of the Internet by socioeconomic characteristics and last time of use. National. Survey on Equipment and Use of Information and Communication Technologies in Households

Table of INEBase Use of the Internet by autonomous communities and cities and last time of use. Autonomous City and Community. Survey on Equipment and Use of Information and Communication Technologies in Households

People are increasingly using the web for fact-checking and other forms of information seeking. The “Google effects” refers to the idea that individuals rely on the Internet as a source of knowledge rather than remembering it for themselves. However, few literature review have yet comprehensively examined the media effects of this intensive Internet search behavior. In this study, by carrying out meta-analysis, we found that google effects is closely associated with cognitive load, behavioral phenotype and cognitive self-esteem. And this phenomenon is also more likely to happen while using a mobile phone to browse the Internet rather than a computer. People with a larger knowledge base are less susceptible to the consequences of Internet use than those with a smaller knowledge base. The media effect was stronger for persons who had used the Internet before than for those who had not. And meta-analyses show that participants in North America (parameter = −1.0365, 95%CI = [−1.8758, −0.1972], p 

this graphs was created in R and Ourdataworld:

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Introduction:

The dawn of the internet era has heralded an unprecedented age of connectivity, transforming the way we live, communicate, and interact on a global scale. As of 2020, approximately 60% of the world's population had access to the internet, marking a significant milestone in the digital revolution. From facilitating seamless communication to enabling cross-border collaborations, the internet has become an indispensable tool in our daily lives. This essay explores the multifaceted impact of the internet across various domains, highlighting its role as a catalyst for global connectivity and innovation.

Communication and Collaboration:

One of the most profound implications of the internet is its ability to bridge geographical distances and facilitate instant communication. Platforms such as email, social media, and messaging apps have revolutionized how we interact with one another, transcending borders and time zones. Whether it's connecting with loved ones halfway across the globe or collaborating with colleagues on a project, the internet has made communication more accessible and efficient than ever before. Video conferencing tools have further enhanced remote collaboration, enabling teams to work seamlessly regardless of their physical location. As a result, businesses have embraced remote work models, unlocking new possibilities for flexibility and productivity.

Financial Inclusion and Remittances:

The internet has democratized access to financial services, empowering individuals to participate in the global economy irrespective of their location. Online banking, mobile payment apps, and digital wallets have revolutionized the way we manage our finances, offering convenience and security. Moreover, the internet has facilitated international money transfers, including remittances, which play a vital role in supporting families and economies worldwide. Platforms like PayPal, TransferWise, and Western Union have streamlined the process of sending and receiving money across borders, reducing transaction costs and increasing efficiency. This newfound accessibility to financial services has contributed to greater financial inclusion and economic empowerment, particularly in underserved communities.

Education and Knowledge Sharing:

The internet has democratized access to education, breaking down traditional barriers to learning and knowledge dissemination. Online courses, tutorials, and educational platforms have made quality education accessible to anyone with an internet connection. Whether it's acquiring new skills, pursuing higher education, or accessing resources for self-improvement, the internet offers a wealth of learning opportunities. Open educational resources (OERs) and Massive Open Online Courses (MOOCs) have revolutionized the way we approach education, fostering a culture of lifelong learning and skill development. Furthermore, online forums and communities provide avenues for knowledge sharing and collaboration, enabling individuals to learn from experts and peers across the globe. This democratization of education holds the promise of narrowing the digital divide and fostering global innovation and prosperity.

Cross-Border Social Connections:

The internet has transcended cultural and linguistic barriers, facilitating cross-border social connections and fostering a sense of global citizenship. Social media platforms have become virtual gathering spaces where people from diverse backgrounds can connect, share experiences, and engage in meaningful dialogue. Whether it's forming friendships with individuals from different countries or participating in online communities centered around shared interests, the internet has enriched our social interactions in unprecedented ways. Moreover, platforms like language exchange forums and cultural exchange programs promote intercultural understanding and empathy, bridging gaps between people of different nationalities and backgrounds. By facilitating cross-border social connections, the internet has the potential to foster a more inclusive and interconnected global comm...

Table of INEBase Use of computer and internet by children aged 10-15 years and place of use in the last 3 months and mobile phone by autonomous communities and cities. Autonomous City and Community. Survey on Equipment and Use of Information and Communication Technologies in Households

Table of INEBase Internet connection and website. National. Survey on the Use of Information and Communication Technologies and Electronic Commerce in Companies

This dataset provides a comprehensive and diverse snapshot of social media users and their engagements across various popular platforms such as Instagram, Twitter, Facebook, YouTube, Pinterest, TikTok, and Spotify. With 100 rows of anonymized data, it offers valuable insights into the dynamic world of social media usage. 😀

Each row in the dataset represents a unique user with a designated User ID and Username to ensure anonymity. Alongside user-specific details, the dataset captures essential information, including the platform being used, the post's content, timestamp, and media type (text, image, or video). Additionally, it tracks engagement metrics such as likes, comments, shares/retweets, and user interactions, providing an overview of the user's popularity and social impact. 💬

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The dataset also includes pertinent user attributes, such as account creation date, privacy settings, number of followers, and following. The users' profiles are further enriched with demographic characteristics, including anonymized representations of their age group and gender. 🗨️

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Hashtags, mentions, media URLs, post URLs, and self-reported location contribute to understanding user interests, content themes, and geographic distribution. Moreover, users' bios and language preferences offer insights into their passions, activities, and linguistic communication on the platforms.

This dataset provides an overview of LinkedIn's user base across the globe. It includes estimates of the number of LinkedIn users in various countries as of 2023 and 2024. The data was sourced from various online reports and analyses of LinkedIn's user demographics.

Description:

The "Daily Social Media Active Users" dataset provides a comprehensive and dynamic look into the digital presence and activity of global users across major social media platforms. The data was generated to simulate real-world usage patterns for 13 popular platforms, including Facebook, YouTube, WhatsApp, Instagram, WeChat, TikTok, Telegram, Snapchat, X (formerly Twitter), Pinterest, Reddit, Threads, LinkedIn, and Quora. This dataset contains 10,000 rows and includes several key fields that offer insights into user demographics, engagement, and usage habits.

Dataset Breakdown:

• Platform: The name of the social media platform where the user activity is tracked. It includes globally recognized platforms, such as Facebook, YouTube, and TikTok, that are known for their large, active user bases.

• Owner: The company or entity that owns and operates the platform. Examples include Meta for Facebook, Instagram, and WhatsApp, Google for YouTube, and ByteDance for TikTok.

• Primary Usage: This category identifies the primary function of each platform. Social media platforms differ in their primary usage, whether it's for social networking, messaging, multimedia sharing, professional networking, or more.

• Country: The geographical region where the user is located. The dataset simulates global coverage, showcasing users from diverse locations and regions. It helps in understanding how user behavior varies across different countries.

• Daily Time Spent (min): This field tracks how much time a user spends on a given platform on a daily basis, expressed in minutes. Time spent data is critical for understanding user engagement levels and the popularity of specific platforms.

• Verified Account: Indicates whether the user has a verified account. This feature mimics real-world patterns where verified users (often public figures, businesses, or influencers) have enhanced status on social media platforms.

• Date Joined: The date when the user registered or started using the platform. This data simulates user account history and can provide insights into user retention trends or platform growth over time.

Context and Use Cases:

• This synthetic dataset is designed to offer a privacy-friendly alternative for analytics, research, and machine learning purposes. Given the complexities and privacy concerns around using real user data, especially in the context of social media, this dataset offers a clean and secure way to develop, test, and fine-tune applications, models, and algorithms without the risks of handling sensitive or personal information.

Researchers, data scientists, and developers can use this dataset to:

• Model User Behavior: By analyzing patterns in daily time spent, verified status, and country of origin, users can model and predict social media engagement behavior.

• Test Analytics Tools: Social media monitoring and analytics platforms can use this dataset to simulate user activity and optimize their tools for engagement tracking, reporting, and visualization.

• Train Machine Learning Algorithms: The dataset can be used to train models for various tasks like user segmentation, recommendation systems, or churn prediction based on engagement metrics.

• Create Dashboards: This dataset can serve as the foundation for creating user-friendly dashboards that visualize user trends, platform comparisons, and engagement patterns across the globe.

• Conduct Market Research: Business intelligence teams can use the data to understand how various demographics use social media, offering valuable insights into the most engaged regions, platform preferences, and usage behaviors.

• Sources of Inspiration: This dataset is inspired by public data from industry reports, such as those from Statista, DataReportal, and other market research platforms. These sources provide insights into the global user base and usage statistics of popular social media platforms. The synthetic nature of this dataset allows for the use of realistic engagement metrics without violating any privacy concerns, making it an ideal tool for educational, analytical, and research purposes.

The structure and design of the dataset are based on real-world usage patterns and aim to represent a variety of users from different backgrounds, countries, and activity levels. This diversity makes it an ideal candidate for testing data-driven solutions and exploring social media trends.

Future Considerations:

As the social media landscape continues to evolve, this dataset can be updated or extended to include new platforms, engagement metrics, or user behaviors. Future iterations may incorporate features like post frequency, follower counts, engagement rates (likes, comments, shares), or even sentiment analysis from user-generated content.

By leveraging this dataset, analysts and data scientists can create better, more effective strategies ...

Table of INEBase No internet access in main dwelling by household size, habitat, net household monthly income and reasons stated. National. Survey on Equipment and Use of Information and Communication Technologies in Households

Publisher Name: Eurostat

This data is gathered by Eurostat and is available in European Commission online for free. you can check it out by this link.

European Union is the covered area in this data set and covers from 2013 to 2021 and is a 44456 * 11 dataset.

This Data Set is containing Social media use by type, internet advertising and size class of enterprise.

This data identifies by isoc_cismt.

Dataset

This dataset was created by Mohamed Ibrahim

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