As of February 2025, English was the most popular language for web content, with over 49.4 percent of websites using it. Spanish ranked second, with six percent of web content, while the content in the German language followed, with 5.6 percent. English as the leading online language United States and India, the countries with the most internet users after China, are also the world's biggest English-speaking markets. The internet user base in both countries combined, as of January 2023, was over a billion individuals. This has led to most of the online information being created in English. Consequently, even those who are not native speakers may use it for convenience. Global internet usage by regions As of October 2024, the number of internet users worldwide was 5.52 billion. In the same period, Northern Europe and North America were leading in terms of internet penetration rates worldwide, with around 97 percent of its populations accessing the internet.

In November 2024, Google.com was the most popular website worldwide with 136 billion average monthly visits. The online platform has held the top spot as the most popular website since June 2010, when it pulled ahead of Yahoo into first place. Second-ranked YouTube generated more than 72.8 billion monthly visits in the measured period. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

As of February 2025, 5.56 billion individuals worldwide were internet users, which amounted to 67.9 percent of the global population. Of this total, 5.24 billion, or 63.9 percent of the world's population, were social media users. Global internet usage Connecting billions of people worldwide, the internet is a core pillar of the modern information society. Northern Europe ranked first among worldwide regions by the share of the population using the internet in 20254. In The Netherlands, Norway and Saudi Arabia, 99 percent of the population used the internet as of February 2025. North Korea was at the opposite end of the spectrum, with virtually no internet usage penetration among the general population, ranking last worldwide. Eastern Asia was home to the largest number of online users worldwide – over 1.34 billion at the latest count. Southern Asia ranked second, with around 1.2 billion internet users. China, India, and the United States rank ahead of other countries worldwide by the number of internet users. Worldwide internet user demographics As of 2024, the share of female internet users worldwide was 65 percent, five percent less than that of men. Gender disparity in internet usage was bigger in African countries, with around a ten percent difference. Worldwide regions, like the Commonwealth of Independent States and Europe, showed a smaller usage gap between these two genders. As of 2024, global internet usage was higher among individuals between 15 and 24 years old across all regions, with young people in Europe representing the most significant usage penetration, 98 percent. In comparison, the worldwide average for the age group 15–24 years was 79 percent. The income level of the countries was also an essential factor for internet access, as 93 percent of the population of the countries with high income reportedly used the internet, as opposed to only 27 percent of the low-income markets.

This dataset contains a sparse graph representing web link structure for a small subset of the Web.

Its a processed version of a single crawl performed by CommonCrawl in 2021 where we strip everything and keep only the link->outlinks structure. The final dataset is basically int -> List[int] format with each integer id representing a url.

Also, in order to increase the value of this resource, we created 6 different version of WebGraph, each varying in the sparsity pattern and locale. We took the following processing steps, in order:

• We started with WAT files from June 2021 crawl.
• Since the outlinks in HTTP-Response-Metadata are stored as relative paths, we convert them to absolute paths using urllib after validating each link.
• To study locale-specific graphs, we further filter based on 2 top level domains: ‘de’ and ‘in’, each producing a graph with an order of magnitude less number of nodes.
• These graphs can still have arbitrary sparsity patterns and dangling links. Thus we further filter the nodes in each graph to have minimum of K ∈ [10, 50] inlinks and outlinks. Note that we only do this processing once, thus this is still an approximation i.e. the resulting graph might have nodes with less than K links.
• Using both locale and count filters, we finalize 6 versions of WebGraph dataset, summarized in the folling table.

All versions of the dataset have following features:

• "row_tag": a unique identifier of the row (source link).
• "col_tag": a list of unique identifiers of non-zero columns (dest outlinks).
• "gt_tag": a list of unique identifiers of non-zero columns used as ground truth (dest outlinks), empty for train/train_t splits.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('web_graph', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

Abstract (en): Knowledge about the general graph structure of this graph is important for designing ranking methods for search engines. To amend the ranking calculated by search engines for different websites, search engine optimization agencies focus on linkage structure for their clients. An extreme appearance of ranking manipulation manifests in spam networks, where pages and websites publishing dubious content try to increase their ratings by setting a massive number of links to other pages and retrieve backlinks. The WDC Hyperlink Graph aggregated by pay-level-domain has been extracted from the Common Crawl 2012 web corpus and covers 43 million pay-level-domains, linked by 623 million connections which have been derived from hyperlinks between the pages contained in the pay-level-domains.

Mobile accounts for approximately half of web traffic worldwide. In the last quarter of 2024, mobile devices (excluding tablets) generated 62.54 percent of global website traffic. Mobiles and smartphones consistently hoovered around the 50 percent mark since the beginning of 2017, before surpassing it in 2020. Mobile traffic Due to low infrastructure and financial restraints, many emerging digital markets skipped the desktop internet phase entirely and moved straight onto mobile internet via smartphone and tablet devices. India is a prime example of a market with a significant mobile-first online population. Other countries with a significant share of mobile internet traffic include Nigeria, Ghana and Kenya. In most African markets, mobile accounts for more than half of the web traffic. By contrast, mobile only makes up around 45.49 percent of online traffic in the United States. Mobile usage The most popular mobile internet activities worldwide include watching movies or videos online, e-mail usage and accessing social media. Apps are a very popular way to watch video on the go and the most-downloaded entertainment apps in the Apple App Store are Netflix, Tencent Video and Amazon Prime Video.

The dynamic face-to-face interaction networks represent the interactions that happen during discussions between a group of participants playing the Resistance game. This dataset contains networks extracted from 62 games. Each game is played by 5-8 participants and lasts between 45--60 minutes. We extract dynamically evolving networks from the free-form discussions using the ICAF algorithm. The extracted networks are used to characterize and detect group deceptive behavior using the DeceptionRank algorithm.

The networks are weighted, directed and temporal. Each node represents a participant. At each 1/3 second, a directed edge from node u to v is weighted by the probability of participant u looking at participant v or the laptop. Additionally, we also provide a binary version where an edge from u to v indicates participant u looks at participant v (or the laptop).

Stanford Network Analysis Platform (SNAP) is a general purpose, high performance system for analysis and manipulation of large networks. Graphs consists of nodes and directed/undirected/multiple edges between the graph nodes. Networks are graphs with data on nodes and/or edges of the network.

The core SNAP library is written in C++ and optimized for maximum performance and compact graph representation. It easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. Besides scalability to large graphs, an additional strength of SNAP is that nodes, edges and attributes in a graph or a network can be changed dynamically during the computation.

SNAP was originally developed by Jure Leskovec in the course of his PhD studies. The first release was made available in Nov, 2009. SNAP uses a general purpose STL (Standard Template Library)-like library GLib developed at Jozef Stefan Institute. SNAP and GLib are being actively developed and used in numerous academic and industrial projects.

http://snap.stanford.edu/data/index.html#face2face

Following the list of websites in ‘.gouv.fr’ generated on the repository GitHub gouvfrlist, here is a list of websites and web services in ‘.gouv.fr’. It made it possible to make a graph representation of domains and subdomains by ministry and administrations (deconcentrated). We also relied on the list of top 250 of administrative procedures and the list of sites en.gouv.fr dating from 2014.

Graphic representation of.gouv.fr websites

Deposit GitHub

The project description and data set are available in the Github repository graph-gouv-en de jbledevehat

Legend

The objects represented are: — The President of the French Republic and the Prime Minister are qualified as “Person” (in blue) — Departments or administrative branches (in yellow) — Websites (in green) — The subdomains of these websites (in orange) — Online services (in red) — Citizen consultation sites (in pink) — Web sites and services either archived or inactive (in black) — Undefined (incoherent) websites (in grey)

Web publications

This representation is available on the application KUMU at the following address:

https://kumu.io/jbledevehat/sites-web-gouvfr#liste-des-sites-web-en-gouvfr-v1

Introduction

Dark Web Statistics: The Dark Web refers to the encrypted portion of the internet that is not indexed by traditional search engines.

It exists as a hidden network that can only be accessed through specific software, configurations, and authorization protocols.

The primary technology used to access the Dark Web is the Tor network, which allows users to maintain anonymity and privacy while accessing websites and services.

The global number of internet users in was forecast to continuously increase between 2024 and 2029 by in total 1.3 billion users (+23.66 percent). After the fifteenth consecutive increasing year, the number of users is estimated to reach 7 billion users and therefore a new peak in 2029. Notably, the number of internet users of was continuously increasing over the past years.Depicted is the estimated number of individuals in the country or region at hand, that use the internet. As the datasource clarifies, connection quality and usage frequency are distinct aspects, not taken into account here.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 internet users in countries like the Americas and Asia.

The Easiest Way to Collect Data from the Internet Download anything you see on the internet into spreadsheets within a few clicks using our ready-made web crawlers or a few lines of code using our APIs

We have made it as simple as possible to collect data from websites

Easy to Use Crawlers Amazon Product Details and Pricing Scraper Amazon Product Details and Pricing Scraper Get product information, pricing, FBA, best seller rank, and much more from Amazon.

Google Maps Search Results Google Maps Search Results Get details like place name, phone number, address, website, ratings, and open hours from Google Maps or Google Places search results.

Twitter Scraper Twitter Scraper Get tweets, Twitter handle, content, number of replies, number of retweets, and more. All you need to provide is a URL to a profile, hashtag, or an advance search URL from Twitter.

Amazon Product Reviews and Ratings Amazon Product Reviews and Ratings Get customer reviews for any product on Amazon and get details like product name, brand, reviews and ratings, and more from Amazon.

Google Reviews Scraper Google Reviews Scraper Scrape Google reviews and get details like business or location name, address, review, ratings, and more for business and places.

Walmart Product Details & Pricing Walmart Product Details & Pricing Get the product name, pricing, number of ratings, reviews, product images, URL other product-related data from Walmart.

Amazon Search Results Scraper Amazon Search Results Scraper Get product search rank, pricing, availability, best seller rank, and much more from Amazon.

Amazon Best Sellers Amazon Best Sellers Get the bestseller rank, product name, pricing, number of ratings, rating, product images, and more from any Amazon Bestseller List.

Google Search Scraper Google Search Scraper Scrape Google search results and get details like search rank, paid and organic results, knowledge graph, related search results, and more.

Walmart Product Reviews & Ratings Walmart Product Reviews & Ratings Get customer reviews for any product on Walmart.com and get details like product name, brand, reviews, and ratings.

Scrape Emails and Contact Details Scrape Emails and Contact Details Get emails, addresses, contact numbers, social media links from any website.

Walmart Search Results Scraper Walmart Search Results Scraper Get Product details such as pricing, availability, reviews, ratings, and more from Walmart search results and categories.

Glassdoor Job Listings Glassdoor Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Glassdoor.

Indeed Job Listings Indeed Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Indeed.

LinkedIn Jobs Scraper Premium LinkedIn Jobs Scraper Scrape job listings on LinkedIn and extract job details such as job title, job description, location, company name, number of reviews, and more.

Redfin Scraper Premium Redfin Scraper Scrape real estate listings from Redfin. Extract property details such as address, price, mortgage, redfin estimate, broker name and more.

Yelp Business Details Scraper Yelp Business Details Scraper Scrape business details from Yelp such as phone number, address, website, and more from Yelp search and business details page.

Zillow Scraper Premium Zillow Scraper Scrape real estate listings from Zillow. Extract property details such as address, price, Broker, broker name and more.

Amazon product offers and third party sellers Amazon product offers and third party sellers Get product pricing, delivery details, FBA, seller details, and much more from the Amazon offer listing page.

Realtor Scraper Premium Realtor Scraper Scrape real estate listings from Realtor.com. Extract property details such as Address, Price, Area, Broker and more.

Target Product Details & Pricing Target Product Details & Pricing Get product details from search results and category pages such as pricing, availability, rating, reviews, and 20+ data points from Target.

Trulia Scraper Premium Trulia Scraper Scrape real estate listings from Trulia. Extract property details such as Address, Price, Area, Mortgage and more.

Amazon Customer FAQs Amazon Customer FAQs Get FAQs for any product on Amazon and get details like the question, answer, answered user name, and more.

Yellow Pages Scraper Yellow Pages Scraper Get details like business name, phone number, address, website, ratings, and more from Yellow Pages search results.

• The tested data for Inter-Domain Path Computation under Domain Uniqueness constraint (IDPCDU).

• On account of no public dataset to be available for the IDPC-NDU problem, two distinct types of instances are created based on the dataset of IDPC-EDU, which is also a shortest-path problem. We first generated three parameters for each instance: number of nodes, number of domains, and number of edges. After that, an optimal path p where the weight of edges is equal to 1 and the number of domains on p is approximately the input graph’s domain number. Next, the noise is added to the instance by for every node in p, besides random weight edges, several random one-weight edges from that node to some other nodes not in p and some random edges with greater values of weight than the total cost of p are added into. These traps make simple greedy algorithms harder to find the optimal solution. Especially in Type 2, feasible paths whose length is less than three are removed. The datasets are categorized into two kinds regarding dimensionality: small instances, each of which has between 50 and 2000 vertices, and large instances, each of which has over 2000 vertices.

• Filename idpc_

First line of a file constains two intergers N and D, which are number of nodes and number of domains, respectively. Second line contains two integers s and t, which are the source node and terminal node. Every next line contains four integers u, v, w, d, represents an edge (u,v) has weight w and belong to domain d.

This graph presents the results of a survey on the number of users of commercial portals for music downloads in Germany from 2018 to 2021. In 2021, there were roughly **** million people among the German-speaking population aged 14 years and older who had used Amazon Prime for downloading music.

Market leader Facebook was the first social network to surpass one billion registered accounts and currently sits at more than three billion monthly active users. Meta Platforms owns four of the biggest social media platforms, all with more than one billion monthly active users each: Facebook (core platform), WhatsApp, Facebook Messenger, and Instagram. In the third quarter of 2023, Facebook reported around four billion monthly core Family product users. The United States and China account for the most high-profile social platforms Most top ranked social networks with more than 100 million users originated in the United States, but services like Chinese social networks WeChat, QQ or video sharing app Douyin have also garnered mainstream appeal in their respective regions due to local context and content. Douyin’s popularity has led to the platform releasing an international version of its network: a little app called TikTok. How many people use social media? The leading social networks are usually available in multiple languages and enable users to connect with friends or people across geographical, political, or economic borders. In 2025, social networking sites are estimated to reach 5.42 billion users and these figures are still expected to grow as mobile device usage and mobile social networks increasingly gain traction in previously underserved markets.

As of February 2025, around 322 million people in the United States accessed the internet, making it one of the largest online markets worldwide. The country currently ranks third after China and India by the online audience size. Overview of internet usage in the United States The digital population in the United States has constantly increased in recent years. Among the most common reasons is the growing accessibility of broadband internet. A big part of the country's digital audience accesses the web via mobile phones. In 2024, the country saw an estimated 97.1 percent mobile internet user penetration. According to a 2024 survey, over 51 percent of U.S. women and 43 percent of men said it is important to them to have mobile internet access anywhere, at any time. Another 41 percent of respondents could not imagine their everyday life without the internet. Google and YouTube are the most visited websites in the country, while music, food, and drinks were the most discussed online topics. Internet usage demographics in the United States While some users can no longer imagine their life without the internet, others do not use it at all. According to 2021 data, 25 percent of U.S. adults 65 and older reported not using the internet. Despite this, online usage was strong across other age groups, especially young adults aged 18 to 49. This age group also reported the highest percentage of smartphone usage in the country as of 2023. Due to a persistent lack of connectivity in rural areas, more online users were based in urban areas of the U.S. than in the countryside.

During the fourth quarter of 2023, the number of daily active users on Facebook reached 2.1 billion, a minor increase on the previous quarter. When compared with the number of daily active users in the final quarter of 2022, the platform has gained around 100 million users. Facebook’s penetration rate for the United States in 2023 was 72.13 percent, up from 71.43 percent in 2022. The social network’s audience reach is projected to stand at 75.79 percent by 2027.

Most popular social media websites

As of May 2021, Facebook was the most used social media site in the United States, accounting for 71.8 percent of all social media visits. Ranking in second place was Pinterest with 12.4 percent, followed by Twitter and Instagram, with 9.15 percent and 3.82 percent, respectively. Although other sites remain popular, Facebook’s number of visits made it undoubtably the leading social media platform in terms of social media site visits.

For Generation Z and Millennials in the United States, Facebook was one of the least popular platforms used to connect with others. Gen Z and Millennials preferred video sharing platforms, specifically Snapchat, TikTok and YouTube.

Meta’s revenue

Facebook Inc was renamed as Meta in 2021, in a strategic step toward the metaverse. Meta Platforms is now the parent company of Facebook, Instagram, Facebook Messenger and WhatsApp amongst others, together being known as Meta’s Family of Apps.

Meta’s annual revenue for 2021 was 117.92 billion U.S. dollars, up from 85.97 billion in 2020. Within a decade, the company has increased its annual revenue by approximately 114 billion U.S. dollars. In the most recent fiscal year, Meta’s Family of Apps were responsible for over 115 billion U.S. dollars’ worth of Meta’s revenue.

The New York Times had **** million digital subscribers as of February 2025, making the publication the global leader in this regard, followed by Substack and The Wall Street Journal with **** million and *** million online news subscribers respectively. Digital subscriptions – the future for news publishers? Subscriptions were cited as the most important digital revenue stream for publishers worldwide in every year from 2021 to 2023, ahead of advertising. As subscriptions have increased, customer retention has also become a growing concern, and according to the aforementioned subscriber losses experienced by The Washington Post, is a well-founded one. Retaining paying members is crucial to achieve growth, and publishers must keep abreast of their users’ needs and industry trends in order to do this. The challenge to achieve sign-ups Converting readers to becoming paying subscribers to news products is challenging. Even video streaming services are experiencing churn. A 2022 survey revealed that ** percent of U.S. subscribers aged 18 to 34 years old canceled between *** and five subscriptions in the three months running up to the survey. If consumers are sacrificing more popular entertainment subscriptions to save money, news subscriptions could also suffer. In fact, ** percent of U.S. subscribers canceled their news subscription* in the last year, a figure which could grow higher as the recession worsens and trust continues to fall.

Zillow reigns supreme in the U.S. real estate website landscape, attracting a staggering ***** million monthly visits in 2024. This figure dwarfs its closest competitor, Realtor.com, which garnered less than half of Zillow's traffic. Online platforms are extremely popular, with the majority of homebuyers using a mobile device during the buying process. The rise of Zillow Founded in 2006, the Seattle-headquartered proptech Zillow has steadily grown over the years, establishing itself as the most popular U.S. real estate website. In 2023, the listing platform recorded about *** million unique monthly users across its mobile applications and website. Despite holding an undisputed position as a market leader, Zillow's revenue has decreased since 2021. A probable cause for the decline is the plummeting of housing transactions and the negative housing sentiment. Performance and trends in the proptech market The proptech market has shown remarkable performance, with companies like Opendoor and Redfin experiencing significant stock price increase in 2023. This growth is particularly notable in the residential brokerage segment. Meanwhile, major players in proptech fundraising, such as Fifth Wall and Hidden Hill Capital, have raised billions in direct investment, further fueling the sector's development. As technology continues to reshape the real estate industry, online platforms like Zillow are likely to play an increasingly crucial role in how people search for and purchase homes. (1477916, 1251604)

As of February 2024, over a third of online users worldwide were aged between 25 and 34 years. Website visitors in this age bracket constituted the biggest group of online users worldwide. Also, 19 percent of global online users were aged 18 to 24 years. The global digital population aged 65 or older represented approximately 4.2 percent of all internet users worldwide. Social media usage and Meta Social media is a major driver of internet use, with a global penetration rate of 62.2 percent. On average, internet users spend 143 minutes per day on social media, highlighting its significant impact on daily online activities. The usage of social media is mostly dominated by Meta platforms, which own four of the largest social media platforms. Facebook leads the ranking with over three billion active users, followed by Instagram and WhatsApp. Instagram's global popularity Meta’s social video platform, Instagram, had long been one of the most engaging social media platforms worldwide, and it was projected to reach 1.44 billion monthly active users. Instagram was particularly favored by users aged 18 to 34, thanks to its ability to offer a variety of interactive content, from images and carousels. This diverse range of content types was a key factor in its popularity among its young user base.

In 2023, most of the global website traffic was still generated by humans but bot traffic is constantly growing. Fraudulent traffic through bad bot actors accounted for 32 percent of global web traffic in the most recently measured period, representing an increase of 1.8 percent from the previous year. Sophistication of Bad Bots on the rise The complexity of malicious bot activity has dramatically increased in recent years. Advanced bad bots have doubled in prevalence over the past two years, indicating a surge in the sophistication of cyber threats. Simultaneously, simple bad bots saw a 6 percent increase compared to the previous year, suggesting a shift in the landscape of automated threats. Meanwhile, areas like entertainment, and law & government face the highest amount of advanced bad bots, with more than 78 percent of their bot traffic affected by evasive applications. Good and bad bots across industries The impact of bot traffic varies across different sectors. Bad bots accounted for over 57.2 percent of the gaming segment's web traffic. Meanwhile, almost half of the online traffic for telecom and ISPs was moved by malicious applications. However, not all bot traffic is considered bad. Some of these applications help index websites for search engines or monitor website performance, assisting users throughout their online search. Therefore, areas like entertainment, food and groceries, and financial services experienced notable levels of good bot traffic, demonstrating the diverse applications of benign automated systems across different sectors.