As of February 2025, China ranked first among the countries with the most internet users worldwide. The world's most populated country had 1.11 billion internet users, more than triple the third-ranked United States, with just around 322 million internet users. Overall, all BRIC markets had over two billion internet users, accounting for four of the ten countries with more than 100 million internet users. Worldwide internet usage As of October 2024, there were more than five billion internet users worldwide. There are, however, stark differences in user distribution according to region. Eastern Asia is home to 1.34 billion internet users, while African and Middle Eastern regions had lower user figures. Moreover, the urban areas showed a higher percentage of internet access than rural areas. Internet use in China China ranks first in the list of countries with the most internet users. Due to its ongoing and fast-paced economic development and a cultural inclination towards technology, more than a billion of the estimated 1.4 billion population in China are online. As of the third quarter of 2023, around 87 percent of Chinese internet users stated using WeChat, the most popular social network in the country. On average, Chinese internet users spent five hours and 33 minutes online daily.

This statistic shows the results of a survey on the usage of Wikipedia in Germany from 2007 to 2014. In 2013, 74 percent of German-speaking internet users reported to visit the online encyclopedia website at least occasionally.

Context :

This dataset provides an overview of global internet users by country between 2021 and 2024, derived from the Wikipedia page "List of countries by number of Internet users." The data includes the total number of internet users in each country, the percentage of the population using the internet, and the population of each country as of 2021. The data was collected from reliable sources like household surveys and internet subscription statistics, providing valuable insights into global connectivity trends.

This dataset can be used to explore digital penetration rates, compare internet adoption by region, and analyze how internet usage has evolved across countries over time. The motivation behind this dataset is to contribute to research on digital inclusion and global technology access.

Introduction

Internet Traffic from Mobile Devices Statistics: More than half of our time online is spent on mobile phones, and wireless Internet has changed the way we use technology. This shift has influenced both devices and apps while also helping digital growth in developing countries. By mid-2024, about 96% of people worldwide were using mobile devices to go online.

The fast increase in mobile internet usage has given businesses and advertisers a better way to promote their brands and reach more people. With mobile traffic growing quickly, just making a website work on mobile is not enough anymore. Competition is stronger, so marketing and content must be designed specifically for mobile users to stay ahead. We shall shed more light on Internet Traffic from Mobile Devices Statistics through this article.

Preprint

Abstract

The World Wide Web is a complex interconnected digital ecosystem, where information and attention flow between platforms and communities throughout the globe. These interactions co-construct how we understand the world, reflecting and shaping public discourse. Unfortunately, researchers often struggle to understand how information circulates and evolves across the web because platform-specific data is often siloed and restricted by linguistic barriers. To address this gap, we present a comprehensive, multilingual dataset capturing all Wikipedia links shared in posts and comments on Reddit from 2020 to 2023, excluding those from private and NSFW subreddits. Each linked Wikipedia article is enriched with revision history, page view data, article ID, redirects, and Wikidata identifiers. Through a research agreement with Reddit, our dataset ensures user privacy while providing a query and ID mechanism that integrates with the Reddit and Wikipedia APIs. This enables extended analyses for researchers studying how information flows across platforms. For example, Reddit discussions use Wikipedia for deliberation and fact-checking which subsequently influences Wikipedia content, by driving traffic to articles or inspiring edits. By analyzing the relationship between information shared and discussed on these platforms, our dataset provides a foundation for examining the interplay between social media discourse and collaborative knowledge consumption and production.

Datasheet

Motivation

The motivations for this dataset stem from the challenges researchers face in studying the flow of information across the web. While the World Wide Web enables global communication and collaboration, data silos, linguistic barriers, and platform-specific restrictions hinder our ability to understand how information circulates, evolves, and impacts public discourse. Wikipedia and Reddit, as major hubs of knowledge sharing and discussion, offer an invaluable lens into these processes. However, without comprehensive data capturing their interactions, researchers are unable to fully examine how platforms co-construct knowledge. This dataset bridges this gap, providing the tools needed to study the interconnectedness of social media and collaborative knowledge systems.

Composition

WikiReddit, a comprehensive dataset capturing all Wikipedia mentions (including links) shared in posts and comments on Reddit from 2020 to 2023, excluding those from private and NSFW (not safe for work) subreddits. The SQL database comprises 336K total posts, 10.2M comments, 1.95M unique links, and 1.26M unique articles spanning 59 languages on Reddit and 276 Wikipedia language subdomains. Each linked Wikipedia article is enriched with its revision history and page view data within a ±10-day window of its posting, as well as article ID, redirects, and Wikidata identifiers. Supplementary anonymous metadata from Reddit posts and comments further contextualizes the links, offering a robust resource for analysing cross-platform information flows, collective attention dynamics, and the role of Wikipedia in online discourse.

Collection Process

Data was collected from the Reddit4Researchers and Wikipedia APIs. No personally identifiable information is published in the dataset. Data from Reddit to Wikipedia is linked via the hyperlink and article titles appearing in Reddit posts.

Preprocessing/cleaning/labeling

Extensive processing with tools such as regex was applied to the Reddit post/comment text to extract the Wikipedia URLs. Redirects for Wikipedia URLs and article titles were found through the API and mapped to the collected data. Reddit IDs are hashed with SHA-256 for post/comment/user/subreddit anonymity.

Uses

We foresee several applications of this dataset and preview four here. First, Reddit linking data can be used to understand how attention is driven from one platform to another. Second, Reddit linking data can shed light on how Wikipedia's archive of knowledge is used in the larger social web. Third, our dataset could provide insights into how external attention is topically distributed across Wikipedia. Our dataset can help extend that analysis into the disparities in what types of external communities Wikipedia is used in, and how it is used. Fourth, relatedly, a topic analysis of our dataset could reveal how Wikipedia usage on Reddit contributes to societal benefits and harms. Our dataset could help examine if homogeneity within the Reddit and Wikipedia audiences shapes topic patterns and assess whether these relationships mitigate or amplify problematic engagement online.

Distribution

The dataset is publicly shared with a Creative Commons Attribution 4.0 International license. The article describing this dataset should be cited: https://doi.org/10.48550/arXiv.2502.04942

Maintenance

Patrick Gildersleve will maintain this dataset, and add further years of content as and when available.

SQL Database Schema

Table: posts

Table: comments

Table: postlinks

Table: commentlinks

In March 2024, close to 4.4 billion unique global visitors had visited Wikipedia.org, slightly down from 4.4 billion visitors since August of the same year. Wikipedia is a free online encyclopedia with articles generated by volunteers worldwide. The platform is hosted by the Wikimedia Foundation.

There are a total of 17 questions in the survey, addressing the following categories:Internet useMobile phone use (smartphones & basic voice/SMS phones)Awareness and use of WikipediaGeneral demographicsThe survey collected 2500 total responses, representing populations in 5 geographical regions served by 3 mobile Iraqi operators. 3 language choices (Arabic, English, Kurdish) were provided.Here are the main questions this survey was designed to answer. However, analyzing the full data set allows you to conduct more in-depth data explorations and gain meaningful insights beyond the points presented here.What is the actual number of people who use the internet?(Real-world behavior makes this difficult to measure from industry reports, since people might have access to the internet through school, friends, internet cafés, public Wifi, etc.)For internet users: What do people mostly use the internet for?For non-internet users: Why not use the internet?How many people use smartphones?Do people with smartphones use the internet from just Wifi? Or just cellular service?How many people think that they don’t use the internet, but still use Facebook or WhatsApp?How many people have heard of Wikipedia? What do they use it for? How often?If they have heard of Wikipedia, but aren’t using it, why not?Compared to previous phone surveys in other countries, the 2017 Iraq phone survey presented new questions.What are people’s awareness of other major internet brands in comparison to Wikipedia?Can people find online content in their preferred language?How does data cost impact internet use?

India phone surveyThere are a total of 19 questions in the survey, addressing the following categories:Internet useMobile phone use (smartphones & basic voice/SMS phones)Awareness and use of WikipediaThe 2016 Indian phone survey is a composite of 7 individual regional surveys. The survey covered over 90% of India's geography, gathering over 9000 full responses from a set of 12 languages presented. Here are the main questions this survey was designed to answer. However, analyzing the full data set allows you to conduct more in-depth data explorations and gain meaningful insights beyond the points presented here:What is the actual number of people who use the internet?(Real-world behavior makes this difficult to measure from industry reports, since people might have access to the internet through school, friends, internet cafés, public Wifi, etc.)For internet users: What do people mostly use the internet for?For non-internet users: Why not use the internet?How many people use smartphones?Do people with smartphones use the internet from just Wifi? Or just cellular service?How many people think that they don’t use the internet, but still use Facebook or WhatsApp?How many people have heard of Wikipedia? What do they use it for? How often?If they have heard of Wikipedia, but aren’t using it, why not?

Enterprise Wiki Software Market Outlook

The global enterprise wiki software market size was valued at USD 1.5 billion in 2023 and is projected to reach USD 3.9 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.2% during the forecast period. This remarkable growth can be attributed to the increasing demand for effective knowledge management solutions that enhance collaboration, knowledge sharing, and information dissemination within enterprises.

One of the primary growth factors contributing to the expansion of the enterprise wiki software market is the growing need for efficient knowledge management systems in organizations. Modern businesses face the challenge of managing vast amounts of information and ensuring that it is accessible to employees when needed. Enterprise wiki software addresses this issue by providing a collaborative platform where information can be organized, updated, and retrieved efficiently. This not only improves productivity but also fosters a culture of knowledge sharing and continuous learning within organizations.

Another significant driver of market growth is the increasing adoption of cloud-based solutions. Cloud-based enterprise wiki software offers several advantages over traditional on-premises systems, including scalability, flexibility, and cost-effectiveness. With cloud-based solutions, organizations can easily scale their wiki platforms to accommodate growing volumes of data and users. Additionally, cloud deployment reduces the need for significant upfront investments in hardware and IT infrastructure, making it an attractive option for small and medium-sized enterprises (SMEs) with limited budgets.

The rise of remote work and distributed teams has also fueled the demand for enterprise wiki software. As more organizations embrace remote work arrangements, there is a growing need for digital tools that facilitate seamless communication and collaboration among geographically dispersed team members. Enterprise wiki software enables employees to access and contribute to shared knowledge repositories from any location, ensuring that critical information is always within reach. This has become particularly important in the wake of the COVID-19 pandemic, which has accelerated the adoption of remote work practices worldwide.

Regionally, North America is expected to dominate the enterprise wiki software market, driven by the presence of major technology companies, high internet penetration, and advanced IT infrastructure. The Asia Pacific region is also anticipated to witness significant growth, fueled by the expanding IT and telecommunications sector, increasing adoption of digital technologies, and growing awareness of the benefits of knowledge management systems. Europe, Latin America, and the Middle East & Africa are also expected to contribute to the market's growth, albeit at a relatively slower pace.

Deployment Type Analysis

Deployment type is a critical segment in the enterprise wiki software market, comprising on-premises and cloud-based solutions. On-premises deployment involves hosting the wiki software on the organization's own servers, providing greater control over data and security. However, this option requires a significant investment in IT infrastructure and ongoing maintenance. Despite these challenges, some large enterprises prefer on-premises solutions due to their stringent security and compliance requirements.

On the other hand, cloud-based deployment offers numerous advantages that have contributed to its increasing popularity. Cloud-based solutions are hosted on third-party servers and accessed via the internet, eliminating the need for organizations to invest in expensive hardware. This deployment model offers enhanced scalability, allowing businesses to easily adjust their storage and user capacities based on demand. Additionally, cloud-based wiki software often includes automatic updates and backups, reducing the burden on internal IT teams and ensuring that the system remains up-to-date with the latest features and security patches.

The flexibility and accessibility of cloud-based solutions make them particularly appealing to SMEs, which may lack the resources to manage and maintain on-premises systems. Cloud deployment enables these smaller organizations to benefit from robust knowledge management tools without the associated high costs. Furthermore, the subscription-based pricing model commonly used for cloud-based software allows for predictable budgeting and lower upfront expenses.

Large

Introduction

VPN Usage Statistics: Virtual Private Networks (VPNs) have transitioned from niche tools for tech-savvy individuals to widely adopted solutions for enhancing online privacy and security. As of 2024, approximately 22.9% of global internet users utilize VPNs for various online activities. In the United States, 46% of adults report using VPNs, equating to around 105 million users. Notably, 95% of American adults are now familiar with VPN technology.

The primary motivations for VPN usage include safeguarding personal data, accessing geo-restricted content, and maintaining anonymity online. Demographically, VPN usage is higher among younger individuals, with 33.1% of males aged 16 to 24 reporting usage. Despite the availability of premium services, 43% of users opt for free VPNs, which may pose security risks. Furthermore, VPN usage is restricted or illegal in several countries, including Belarus, Iran, Iraq, North Korea, and Turkmenistan. These statistics underscore the growing reliance on VPNs as essential tools for digital privacy and security in an increasingly connected world.

Nigeria phone survey 2016In the spring of 2016, the Wikimedia Foundation partnered with a phone survey company and conducted a large-scale survey to learn more about technology and Wikipedia use in Nigeria.The 19 questions in the survey covered:* Internet use* Mobile phone use (smartphones & basic voice/SMS phones)* Awareness and use of Wikipedia* General demographicsThis was a large-scale IVR phone survey, gathering over 2700 completed survey responses from randomly generated numbers across Nigeria. Voice (IVR) surveys were chosen to include respondents who may not have internet access. This approach allowed us to measure internet and smartphone penetration, along with answering other Wikipedia related questions. Also, the scale and methodology of the survey kept the margin of error low (

Introduction

Digital Footprint Statistics: A digital footprint is the trail of information people leave behind when using the internet. It includes everything from social media posts to online searches, websites visited, and emails sent. Some of this data is shared intentionally, like posting on Facebook, while other parts are collected automatically, like tracking cookies from websites.

A digital footprint can be active, meaning data is shared by choice, or passive, meaning it is collected without you realizing it. It's important to manage your digital footprint because it can affect your privacy, reputation, and even job opportunities in the future. Understanding it helps you stay safe online.

This set of data is the result of a joint Web QoE work conducted by the Telecom Paris researchers and the Wikimedia Foundation (https://meta.wikimedia.org/wiki/Research:Study_of_performance_perception_on_Wikimedia_projects, https://webqoe.telecom-paristech.fr/ ).Both the datasets contain the user answers to the survey question appeared to the French and Russian Wikipedias during the time span ranging from 25/05/2018 to 15/10/2018. The first file ("wikiqoe_datetime.csv") contains three columns each one indicating respectively for every record: - the wiki of the page for which the user answer to the survey has been collected (either French or Russian), - the time rounded to the hour (in order to prevent user deanonymization) as a datetime object, - the survey response provided by the user (positive = 1, negative = -1, neutral = 0).The second file ("wikiqoe_public_available_features.csv") contains 20 columns each one indicating respectively for every record:- the wiki from which the request was issued (ruwiki or frwiki),- 18 performance metrics (e.g., fetchStart, domInteractive, etc.),- the survey response provided by the user (positive = 1, negative = -1, neutral = 0).Note that the two dataset comprise the same set of users, but, for the second one, the time information is not provided, in order to avoid potential deanonymization using other (unknown) dataset.The Wikimedia legal team has given clearance for the publication of these datasets, after having fully prevented user deanonymization and content-linkability.More information and details regarding methodology and results can be found in the papers and in the technical report stored here: https://webqoe.telecom-paristech.fr/If you use these datasets in your research, you can reference to the appropriate paper(s):1) @inproceedings{salutari19www,title = {A large-scale study of Wikipedia users’ quality of experience},author = {Salutari, Flavia and Hora, Diego Da and Dubuc, Gilles and Rossi, Dario},booktitle = {In proceedings of the 30th Web Conference (WWW'19)},address = {San Francisco, CA, USA},month = may,year = {2019},howpublished = {https://nonsns.github.io/paper/rossi19www.pdf}}

Context

From the beginning of 2020 to April 8th (the day Wuhan reopened), this dataset summarizes the social media hotspots and what people focused in the mainland of China, as well as the epidemic development trend during this period. The dataset containing four .csv files covers most social media platforms in the mainland: Sina Weibo, TikTok, Toutiao and Douban.

Sina Weibo

a platform based on fostering user relationships to share, disseminate and receive information. Through either the website or the mobile app, users can upload pictures and videos publicly for instant sharing, with other users being able to comment with text, pictures and videos, or use a multimedia instant messaging service. The company initially invited a large number of celebrities to join the platform at the beginning, and has since invited many media personalities, government departments, businesses and non-governmental organizations to open accounts as well for the purpose of publishing and communicating information. To avoid the impersonation of celebrities, Sina Weibo uses verification symbols; celebrity accounts have an orange letter "V" and organizations' accounts have a blue letter "V". Sina Weibo has more than 500 million registered users;[12] out of these, 313 million are monthly active users, 85% use the Weibo mobile app, 70% are college-aged, 50.10% are male and 49.90% are female. There are over 100 million messages posted by users each day. With 90 million followers, actress Xie Na holds the record for the most followers on the platform. Despite fierce competition among Chinese social media platforms, Sina Weibo has proven to be the most popular; part of this success may be attributable to the wider use of mobile technologies in China.[https://en.wikipedia.org/wiki/Sina_Weibo]

Douyin

Douyin (English: TikTok), referred to as TikTok, is a short-video social application on mobile phones. Users can record 15-second short videos, which can easily complete mouth-to-mouth (to mouth), and built-in special effects The user can leave a message to the video. Since September 2016, Toutiao has been launched online and is positioned as a short music video community suitable for Chinese young people. The application is vertical music UGC short videos, and the number of users has grown rapidly since 2017. In June 2018, Douyin reached 500 million monthly active users worldwide and 150 million daily active users in China. [https://zh.wikipedia.org/wiki/%E6%8A%96%E9%9F%B3]

Toutiao

Toutiao or Jinri Toutiao is a Chinese news and information content platform, a core product of the Beijing-based company ByteDance. By analyzing the features of content, users and users’ interaction with content, the company's algorithm models generate a tailored feed list of content for each user. Toutiao is one of China's largest mobile platforms of content creation, aggregation and distribution underpinned by machine learning techniques, with 120 million daily active users as of September 2017. [https://en.wikipedia.org/wiki/Toutiao]

Douban

Douban.com (Chinese: 豆瓣; pinyin: Dòubàn), launched on March 6, 2005, is a Chinese social networking service website that allows registered users to record information and create content related to film, books, music, recent events, and activities in Chinese cities. It could be seen as one of the most influential web 2.0 websites in China. Douban also owns an internet radio station, which ranks No.1 in the iOS App Store in 2012. Douban was formerly open to both registered and unregistered users. For registered users, the site recommends potentially interesting books, movies, and music to them in addition to serving as a social network website such as WeChat, Weibo and record keeper; for unregistered users, the site is a place to find ratings and reviews of media. Douban has about 200 million registered users as of 2013. The site serves pan-Chinese users, and its contents are in Chinese. It covers works and media in Chinese and in foreign languages. Some Chinese authors and critics register their official personal pages on the site. [https://en.wikipedia.org/wiki/Douban]

Content

Weibo realTimeHotSearchList can be regarded as a platform for gathering celebrity gossip, social life and major news. In this document, I collect the top 50 topics of the hot search list every 12 hours during the day, so there are 100 hot topics each day. These topics are converted into English by Google translation, although the translation effect is not ideal due to sentence segmentation and language background deviation. In this document, I created a new column ['Coron-Related ( 1 yes, 0 not ) '] to mark topics related to the new crown, if relevant, it is marked as 1, if not then marked empty or 0. The google translation is extremely inaccurate (so maybe google the Chinese title to confirm is the best bet...

About this record This data supports "WikiProject Clinical Trials for Wikidata", a preprint at https://doi.org/10.1101/2022.04.01.22273328 . The files in this record are a snapshot of the content output and appearance of WikiProject Clinical Trials in February 2022. Access the project at https://www.wikidata.org/wiki/Wikidata:WikiProject_Clinical_Trials . The Jupyter Notebook in this record (1 WikiProject Clinical Trials 2022-02.ipynb) contains the project's example SPARQL queries from call Wikidata content, and the data files are the present results from those queries. As anyone can edit Wikidata and its content grows with time, query results will change over time. Background Wikidata is a community and database within the Wikipedia ecosystem. WikiProject Clinical Trials is a community project in Wikidata to curate data related to clinical trials for its use in the Wikimedia platform or export to elsewhere. Queries 1 Model profiles 1.1 Clinical trials for Zika fever 1.2 Clinical trials using COVID-19 vaccine 1.3 Clinical trials at Vanderbilt University 1.4 Clinical trials with Julie McElrath as principal investigator 1.5 Clinical trials funded by Patient-Centered Outcomes Research Institute 2 Topics by count of clinical trials 2.1 Medical conditions 2.2 Research interventions 2.3 Research sites 2.4 Principal investigators 2.5 Funders 3 Organizational affiliations 3.1 Clinical trials with principal investigator and their affiliation 3.2 Clinical trials where principal investigator has Vanderbilt University affiliation 3.3 Chart of organizations by count of clinical trials 3.4 Clinical trials where the sponsor was Pfizer 4 Researcher demographics 4.1 Count of principal investigators by gender 4.2 Clinical trials where the principal investigator is female 4.3 Principal investigators by occupation 5 Scope of Wikidata's clinical trials content 5.1 List of clinical trials 5.2 Count of clinical trials 5.3 Most common properties applied to clinical trials 5.4 Count of statements in clinical trial records 5.5 Count of trial records in Wikidata per clinical trial registry Online access Again, the project at Wikidata is at https://www.wikidata.org/wiki/Wikidata:WikiProject_Clinical_Trials . The Wikidata Query Service accessible through the "Query" page there assists users in modifying these or any queries to search for different targets, such as other medical conditions or institutions of interest. Another way to access the content online is by accessing the notebook through a copy in GitHub, such as at https://github.com/bluerasberry/WikiProject-Clinical-Trials and rendering it through an online viewer, such as https://mybinder.org , or use the direct link https://mybinder.org/v2/zenodo/10.5281/zenodo.6317047/ . Images While Wikidata does retain historical versions which should be perpetually archived and available through the project page, this record contains image screenshots of the project as it appears now. For additional image metadata visit the image archives in Wikimedia Commons as linked here: https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_screenshot_2022-02.png https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_home.png https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_model.png https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_query.png https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_curate.png https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_about.png https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_talk.png https://commons.wikimedia.org/wiki/File:Noun_clinical_benchmarking_1958245.svg, image by Bold Yellow supported by Wellcome Trust grant 219706/Z/19/Z

Introduction

Dark Web Statistics: Today, the internet consists of three parts: the surface web, the deep web, and the dark web. The dark web is the hidden part of the internet. Users can not access it normally by surfing the internet. The dark Web consists of illegal selling activities such as credit card numbers, bank login details, weapons, hacked social media accounts, weapons, drugs, and much more.

Although for some people, it is interesting to check out such things on the dark web, it should be avoided to go to such places on the internet. Through these recent Dark Web Statistics, let’s understand in detail what the dark web means.

Structural equation modeling for notified cases of Chikungunya virus (adjusted model).

Structural equation modeling for notified cases of Chikungunya virus (unadjusted model).

As of December 2023, the English subdomain of Wikipedia had around 6.91 million articles published, being the largest subdomain of the website by number of entries and registered active users. German and French ranked third and fourth, with over 29.6 million and 26.5 million entries. Being the only Asian language figuring among the top 10, Cebuano was the language with the second-most articles on the portal, amassing around 6.11 million entries. However, while most Wikipedia articles in English and other European languages are written by humans, entries in Cebuano are reportedly mostly generated by bots.

Introduction

Skype Statistics: In today’s digital age, communication tools are integral to personal and professional interactions. As a pioneering platform for Voice over Internet Protocol (VoIP), Skype has led this revolution since its establishment in 2003. Within a short time after it was introduced as one of the pioneer platforms for free voice and video calls over the Internet, Skype had millions of users around the world. Its functionality has grown to allow file sharing, instant messaging, and even conference calling, making it a one-stop shop for both individuals and organizations.

Skype has played an undeniable role in global communication. Whether it be linking up families who live far apart or enabling international business meetings, Skype has changed how we connect. The fact of the matter is that the platform serves as a facilitator for professional interaction and collaboration. The changing nature of Skype statistics has important messages for both business and private persons as we make our way through the rapid movement of electronic communication.

This article aims to provide statistics about Skype, investigating who uses this software, when they use it most often, and its place within the larger context of digital communication.