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.

This Website Statistics dataset has four resources showing usage of the Lincolnshire Open Data website. Web analytics terms used in each resource are defined in their accompanying Metadata file.

• Website Usage Statistics: This document shows a statistical summary of usage of the Lincolnshire Open Data site for the latest calendar year.

• Website Statistics Summary: This dataset shows a website statistics summary for the Lincolnshire Open Data site for the latest calendar year.

• Webpage Statistics: This dataset shows statistics for individual Webpages on the Lincolnshire Open Data site by calendar year.

• Dataset Statistics: This dataset shows cumulative totals for Datasets on the Lincolnshire Open Data site that have also been published on the national Open Data site Data.Gov.UK - see the Source link.

  Note: Website and Webpage statistics (the first three resources above) show only UK users, and exclude API calls (automated requests for datasets). The Dataset Statistics are confined to users with javascript enabled, which excludes web crawlers and API calls.

These Website Statistics resources are updated annually in January by the Lincolnshire County Council Business Intelligence team. For any enquiries about the information contact opendata@lincolnshire.gov.uk.

Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly

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.

When asked about "Attitudes towards the internet", most Japanese respondents pick "I'm concerned that my data is being misused on the internet" as an answer. 35 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

Internet use in the UK annual estimates by age, sex, disability, ethnic group, economic activity and geographical location, including confidence intervals.

This Website Statistics dataset has three resources showing usage of the Lincolnshire Open Data website. Web analytics terms used in each resource are defined in their accompanying Metadata file. Please Note: due to a change in Analytics platform and accompanying metrics, the current files do not contain a full years data. The files will be updated again in January 2025 with 2024-2025 data. The previous dataset containing Web Analytics has been archived and can be found in the following link; https://lincolnshire.ckan.io/dataset/website-statistics-archived - Website Usage Statistics: This document shows a statistical summary of usage of the Lincolnshire Open Data site for the latest calendar year. - Website Statistics Summary: This dataset shows a website statistics summary for the Lincolnshire Open Data site for the latest calendar year. - Webpage Statistics: This dataset shows statistics for individual Webpages on the Lincolnshire Open Data site by calendar year. Note: The resources above exclude API calls (automated requests for datasets). These Website Statistics resources are updated annually in February by the Lincolnshire County Council Open Data team.

Digital technology and Internet use, website traffic strategies, by North American Industry Classification System (NAICS) and size of enterprise for Canada from 2012 to 2013.

Code:

Packet_Features_Generator.py & Features.py

To run this code:

pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j

-h, --help show this help message and exit -i TXTFILE input text file -x X Add first X number of total packets as features. -y Y Add first Y number of negative packets as features. -z Z Add first Z number of positive packets as features. -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,... -s S Generate samples using size s. -j

Purpose:

Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.

Uses Features.py to calcualte the features.

startMachineLearning.sh & machineLearning.py

To run this code:

bash startMachineLearning.sh

This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags

Options (to be edited within this file):

--evaluate-only to test 5 fold cross validation accuracy

--test-scaling-normalization to test 6 different combinations of scalers and normalizers

Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use

--grid-search to test the best grid search hyperparameters - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:' - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'

Purpose:

Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.

Data

Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.

Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:

First number is a classification number to denote what website, query, or vr action is taking place.

The remaining numbers in each line denote:

The size of a packet,

and the direction it is traveling.

negative numbers denote incoming packets

positive numbers denote outgoing packets

Figure 4 Data

This data uses specific lines from the Virtual Reality.txt file.

The action 'LongText Search' refers to a user searching for "Saint Basils Cathedral" with text in the Wander app.

The action 'ShortText Search' refers to a user searching for "Mexico" with text in the Wander app.

The .xlsx and .csv file are identical

Each file includes (from right to left):

The origional packet data,

each line of data organized from smallest to largest packet size in order to calculate the mean and standard deviation of each packet capture,

and the final Cumulative Distrubution Function (CDF) caluclation that generated the Figure 4 Graph.

Introduction

Buffer vs Hootsuite Statistics: Buffer and Hootsuite are working against each other for supremacy in scheduling, analytics, collaboration, and affordability. Buffer offers simple interfaces and transparent pricing for creators and small and medium enterprises. Hootsuite markets to larger enterprises for deep analytics, bulk management tools, and integrations comprising its internal operations.

This comprehensive Buffer vs Hootsuite statistics focuses on user growth, satisfaction, pricing, features, and ease of use, all backed by numbers and insights from various sources. So, by the end, you will have an informative and data-driven sense of what platform will suit your needs better.

When asked about "Attitudes towards the internet", most Mexican respondents pick "It is important to me to have mobile internet access in any place" as an answer. 56 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

This is a dataset of Tor cell file extracted from browsing simulation using Tor Browser. The simulations cover both desktop and mobile webpages. The data collection process was using WFP-Collector tool (https://github.com/irsyadpage/WFP-Collector). All the neccessary configuration to perform the simulation as detailed in the tool repository.The webpage URL is selected by using the first 100 website based on: https://dataforseo.com/free-seo-stats/top-1000-websites.Each webpage URL is visited 90 times for each deskop and mobile browsing mode.

TagX Web Browsing Clickstream Data: Unveiling Digital Behavior Across North America and EU Unique Insights into Online User Behavior TagX Web Browsing clickstream Data offers an unparalleled window into the digital lives of 1 million users across North America and the European Union. This comprehensive dataset stands out in the market due to its breadth, depth, and stringent compliance with data protection regulations. What Makes Our Data Unique?

Extensive Geographic Coverage: Spanning two major markets, our data provides a holistic view of web browsing patterns in developed economies. Large User Base: With 300K active users, our dataset offers statistically significant insights across various demographics and user segments. GDPR and CCPA Compliance: We prioritize user privacy and data protection, ensuring that our data collection and processing methods adhere to the strictest regulatory standards. Real-time Updates: Our clickstream data is continuously refreshed, providing up-to-the-minute insights into evolving online trends and user behaviors. Granular Data Points: We capture a wide array of metrics, including time spent on websites, click patterns, search queries, and user journey flows.

Data Sourcing: Ethical and Transparent Our web browsing clickstream data is sourced through a network of partnered websites and applications. Users explicitly opt-in to data collection, ensuring transparency and consent. We employ advanced anonymization techniques to protect individual privacy while maintaining the integrity and value of the aggregated data. Key aspects of our data sourcing process include:

Voluntary user participation through clear opt-in mechanisms Regular audits of data collection methods to ensure ongoing compliance Collaboration with privacy experts to implement best practices in data anonymization Continuous monitoring of regulatory landscapes to adapt our processes as needed

Primary Use Cases and Verticals TagX Web Browsing clickstream Data serves a multitude of industries and use cases, including but not limited to:

Digital Marketing and Advertising:

Audience segmentation and targeting Campaign performance optimization Competitor analysis and benchmarking

E-commerce and Retail:

Customer journey mapping Product recommendation enhancements Cart abandonment analysis

Media and Entertainment:

Content consumption trends Audience engagement metrics Cross-platform user behavior analysis

Financial Services:

Risk assessment based on online behavior Fraud detection through anomaly identification Investment trend analysis

Technology and Software:

User experience optimization Feature adoption tracking Competitive intelligence

Market Research and Consulting:

Consumer behavior studies Industry trend analysis Digital transformation strategies

Integration with Broader Data Offering TagX Web Browsing clickstream Data is a cornerstone of our comprehensive digital intelligence suite. It seamlessly integrates with our other data products to provide a 360-degree view of online user behavior:

Social Media Engagement Data: Combine clickstream insights with social media interactions for a holistic understanding of digital footprints. Mobile App Usage Data: Cross-reference web browsing patterns with mobile app usage to map the complete digital journey. Purchase Intent Signals: Enrich clickstream data with purchase intent indicators to power predictive analytics and targeted marketing efforts. Demographic Overlays: Enhance web browsing data with demographic information for more precise audience segmentation and targeting.

By leveraging these complementary datasets, businesses can unlock deeper insights and drive more impactful strategies across their digital initiatives. Data Quality and Scale We pride ourselves on delivering high-quality, reliable data at scale:

Rigorous Data Cleaning: Advanced algorithms filter out bot traffic, VPNs, and other non-human interactions. Regular Quality Checks: Our data science team conducts ongoing audits to ensure data accuracy and consistency. Scalable Infrastructure: Our robust data processing pipeline can handle billions of daily events, ensuring comprehensive coverage. Historical Data Availability: Access up to 24 months of historical data for trend analysis and longitudinal studies. Customizable Data Feeds: Tailor the data delivery to your specific needs, from raw clickstream events to aggregated insights.

Empowering Data-Driven Decision Making In today's digital-first world, understanding online user behavior is crucial for businesses across all sectors. TagX Web Browsing clickstream Data empowers organizations to make informed decisions, optimize their digital strategies, and stay ahead of the competition. Whether you're a marketer looking to refine your targeting, a product manager seeking to enhance user experience, or a researcher exploring digital trends, our cli...

Introduction

Tor Statistics: Tor is a free network that helps people stay anonymous online. It works using open-source software and depends on more than 7,000 volunteer-run relays across the world. Tor, known as “The Onion Router,†is a free tool that helps protect your identity and activity online.

It helps in hiding location and internet use by passing your data through many different servers, called relays, run by volunteers around the globe. Tor is built on open-source software and is widely used by journalists, activists, and everyday users who value their privacy. It was developed by the Tor Project and initially released on September 20, 2002.

This article includes several statistical analyses from different sources covering the overall market trend, features, types, user bases, demographics, countries, traffic shares, and many other factors.

Web traffic statistics for the top 2000 most visited pages on nyc.gov by month.

When asked about "Attitudes towards the internet", most Chinese respondents pick "It is important to me to have mobile internet access in any place" as an answer. 48 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

Aggregate data of sessions, users etc. for www.sahealth.sa.gov.au Aggregate data of sessions, users etc. for www.sahealth.sa.gov.au

Comprehensive analysis of Amazon's daily website traffic including visitor counts, traffic sources, mobile vs desktop usage, and seasonal patterns based on May 2025 data.

As cliché as it sounds at this point, the internet is an integral part of our lives. Most of us spend more time on the internet than speaking to people in the real world. This paradigm shift is reflected in internet usage across the globe. This article has covered some...

Introduction

Bluehost vs SiteGround Statistics: Bluehost and SiteGround are two commonly used web hosting providers, which are crucial for building a fast, secure, and reliable website. Bluehost is a web hosting and domain registration company that sells shared hosting, WordPress hosting, VPS hosting, dedicated hosting, and WooCommerce hosting, as well as professional marketing services. In contrast, SiteGround is a web hosting company that provides shared hosting, cloud hosting, enterprise solutions, email hosting, and domain registration.

This article presents several statistical analyses from various perspectives, including market analysis, unique features, user base, usage, pricing, speed, scalability, and backend technology. Go through the overall analysis; you will gain a clear idea of how to choose a better option based on users' needs.