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.

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.

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 people from Czech are publishing a dataset for the HTTPS traffic classification.

Since the data were captured mainly in the real backbone network, they omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

During research, they divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

They have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. They also used several popular websites that primarily focus on the audience in Czech. The identified traffic classes and their representatives are provided below:

Live Video Stream Twitch, Czech TV, YouTube Live Video Player DailyMotion, Stream.cz, Vimeo, YouTube Music Player AppleMusic, Spotify, SoundCloud File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive Website and Other Traffic Websites from Alexa Top 1M list

In November 2024, Google.com was the most popular website worldwide with approximately 6.25 billion unique monthly visitors. YouTube.com was ranked second with an estimated 3.64 billion unique monthly visitors. Both websites are among the most visited websites worldwide.

Google Search Statistics 2023

• Google is the most searched website in the World.
• Google receives more visitors than any other site. Google is accessed 89.3 trillion times per month.
• Google is used by billions of people every day to conduct their searches. Google is much more than a simple search engine.
• Google provides many other services. Google Shopping and Google News also feature. Google Mail, Google's popular email service, is included.
• Google organic search traffic is 16.3% of the total US searches.

In November 2024, Google.com was the most visited website in the United States, with over 25 billion total visits. YouTube.com came in second with 12 billion total visits. Reddit.com and Amazon.com counted approximately 3.12 billion and 2.89 monthly visits each from U.S. online audiences.

We are publishing a dataset we created for the HTTPS traffic classification.

Since the data were captured mainly in the real backbone network, we omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

During our research, we divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

We have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. We also used several popular websites that primarily focus on the audience in our country. The identified traffic classes and their representatives are provided below:

Live Video Stream Twitch, Czech TV, YouTube Live

Video Player DailyMotion, Stream.cz, Vimeo, YouTube

Music Player AppleMusic, Spotify, SoundCloud

File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive

Website and Other Traffic Websites from Alexa Top 1M list

The DNS over HTTPS (DoH) is becoming a default option for domain resolution in modern privacy-aware software. Therefore, research has already focused on various aspects; however, a comprehensive dataset from an actual production network is still missing. In this paper, we present a novel dataset, which comprises multiple PCAP files of DoH traffic. The captured traffic is generated towards various DoH providers to cover differences of various DoH server implementations and configurations. In addition to generated traffic, we also provide real network traffic captured on high-speed backbone lines of a large Internet Service Provider with around half a million users. Network identifiers (excluding network identifiers of DoH resolvers) in the real network traffic (e.g., IP addresses and transmitted content) were anonymized, but still, the important characteristics of the traffic can still be obtained from the data that can be used, e.g., for network traffic classification research. The real network traffic dataset contains DoH and also non-DoH HTTPS traffic as observed at the collection points in the network.

This repository provides supplementary files for the "Collection of Datasets with DNS over HTTPS Traffic" :

─── supplementary_files | - Directory with supplementary files (scripts, DoH resolver list) used for dataset creation ├── chrome | - Generation scripts for Chrome browser and visited websites during generation ├── doh_resolvers | - The list of DoH resolvers used for filter creation during ISP backbone capture ├── firefox | - Generation scripts for Firefox browser and visited websites during generation └── pcap-anonymizer | - Anonymization script of real backbone captures

Collection of datasets:

DoH-Gen-F-AABBC --- https://doi.org/10.5281/zenodo.5957277

DoH-Gen-F-FGHOQS --- https://doi.org/10.5281/zenodo.5957121

DoH-Gen-F-CCDDD --- https://doi.org/10.5281/zenodo.5957420

DoH-Gen-C-AABBCC --- https://doi.org/10.5281/zenodo.5957465

DoH-Gen-C-DDD -- https://doi.org/10.5281/zenodo.5957676

DoH-Gen-C-CFGHOQS --- https://doi.org/10.5281/zenodo.5957659

DoH-Real-world --- https://doi.org/10.5281/zenodo.5956043

As many general retailers or mass distribution channels experienced an exponential growth during the months of the COVID-19 induced lockdown in France, the source wanted to measure the share of organic traffic of the different retailers websites. Thus, we note that around ** percent of visits to Franprix.fr came from organic traffic, that is to say, visits coming from search engines such as Google or Bing. The “minor” competitors in the sector have clearly understood that the fight against the big names (and their direct traffic) requires an elaborate keyword strategy.

aliexpress.com is ranked #18 in KR with 765.79M Traffic. Categories: Retail, Online Services. Learn more about website traffic, market share, and more!

For detailed information regarding the Traffic API, see the Interactive Traffic Map website from the Traffic and Parking website.Traffic WebCam APIProvides images for the City of Ottawa’s traffic web cams. These images are available at sixty second intervals and are approximately 30-50KB in size. To access the images users will be required to have an access key. The application form for access keys can be found on this page: http://trafficopendata.ottawa.ca/ts/rsadmin/certificate.jsp

After completing the registration form and receiving a confirmation email with a certificate number you will be able to access the camera images. To access a camera image you can access the URL http://traffic.ottawa.ca/opendata/camera with the following parameters:

Camera number Certificate: The certificate string as supplied in the confirmation email. Id: User Id (optional).

Note: City of Ottawa cameras have camera numbers less than 2000, and MTO cameras have camera numbers greater than 2000.

Note: The Id is a string value assigned by your user to each user or instance of your application accessing the images. The Id must be alphanumeric characters [a-z, A-Z, 0-9]. A given user id for a given certificate may only access the cameras at intervals of at least 60 seconds.

e.g. To access City Camera 16 (Bank and Hunt Club) -- http://traffic.ottawa.ca/opendata/camera?c=16&certificate=CERT123&id=2

e.g. To access MTO Camera 2002 (St Laurent) -- http://traffic.ottawa.ca/opendata/camera?c=2002&certificate=CERT123&id=1

The images Getting Camera Numbers

To obtain a list of camera numbers you can access a JSON list of the available cameras: http://traffic.ottawa.ca/map/camera_list

More information about the format of the list can be found in the following document: http://traffic.ottawa.ca/map/opendata_info

Accuracy: There are no known errors associated with these images. Update Frequency: N/A - API delivers most up to date information available.Contact: Motaz Aladas

The census count of vehicles on city streets is normally reported in the form of Average Daily Traffic (ADT) counts. These counts provide a good estimate for the actual number of vehicles on an average weekday at select street segments. Specific block segments are selected for a count because they are deemed as representative of a larger segment on the same roadway. ADT counts are used by transportation engineers, economists, real estate agents, planners, and others professionals for planning and operational analysis. The frequency for each count varies depending on City staff’s needs for analysis in any given area. This report covers the counts taken in our City during the past 12 years approximately.

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)

Lead list provide valuable insights into the software industry. Essential for market research and competitor analysis.

Find new prospects by the technologies they use. Lead lists contain websites, email addresses, phone numbers and social media profiles. Create and export custom reports for any web technology based on website traffic, location and language.

Get started by selecting one or more technologies. Optionally add filters and limits to customise your list.

amazon.in is ranked #7 in IN with 237.37M Traffic. Categories: Retail, Online Services. Learn more about website traffic, market share, and more!

Global visitors to sephora.com in April 2024 were most likely to be between the ages of ** and **. This age group accounted for over a third of website visitors. The second-most popular age group on sephora.com were ** to 44-year-olds, who accounted for around ** percent of traffic to the website. Sephora's journey to global recognition Sephora is a giant of cosmetic and beauty products, and in 2023, it was able to achieve the highest revenue among online beauty stores, surpassing big names such as Ulta and Shiseido. The brand was first launched in 1970 and went online for the first time in 1999 in the United States. This was an important milestone for the brand, as it helped Sephora expand its reach beyond its physical locations and begin to build its presence in e-commerce, which was just starting to take off at the time. The Sephora shopper There are other metrics that are known about the typical Sephora shopper in the U.S., aside from the age groups that visit Sephora.com the most. Recent research shows that Sephora customers make on average ****** U.S. dollars per year. This is slightly less than Ulta shoppers at ******* USD, but more than Target shoppers at ****** USD. Sephora.com visitors are also mostly female, with women accounting for a whopping *********** of all visits. Regarding Sephora shoppers' social media use for beauty inspiration, TikTok is where they like to scroll. In 2023, around ** percent of Sephora shoppers said they mostly used TikTok to find information about beauty products, brands, and techniques.

In December 2023, Amazon.com was the leading online shopping website in the United States. During the measured period, the sprawling platform accounted for over 45 percent of desktop traffic in the e-commerce and shopping subcategory. In second place on the list was eBay.com, with 9.22 percent of visitors. Walmart ranked third with a bit less than six percent of web traffic. Why customers browse on Amazon The main reason behind the outstanding online traffic to Amazon is user behavior throughout the customer journey. Amazon serves as a search engine for U.S. consumers, with 73 percent browsing it for inspiration and product discovery. Another 65 percent of U.S. shoppers landed on Amazon to look for products and compare products. In turn, Google is left third in the ranking of most used platforms. Generational differences In the beauty segment, the customer journey is more likely to start on Amazon among senior consumers. In the United States, 44 percent of Baby Boomers started their search of beauty products on the marketplace, while only 35 percent of Gen Z consumers reported doing the same.

In November 2024, Google.com held the top spot in India's website rankings, averaging over **** billion monthly visits. YouTube ranked second, with traffic of **** billion visits, while social platforms Instagram.com and Facebook.com followed with *** million and *** million monthly visits each. Internet penetration In the past decade, India has witnessed a remarkable transformation in its digital landscape. This substantial expansion has resulted in extensive digital connectivity, with more than **** of India's *** billion citizens now enjoying internet access. India ranked **** on the Digital Quality of Life Index in 2023, which revealed electronic infrastructure as one of the country’s strengths. YouTube in India As of 2025, India had the world’s largest YouTube user base, figuring over *** million users. The video platform caters to the nation’s tech-savvy denizens as an educational resource and a source of entertainment. Moreover, YouTube has evolved into a dynamic space for digital marketing, especially harnessing the consumer base segment aged below 32 years.

Between September and November 2023, Google.com ranked as the most visited website in Ghana, with an average of nearly ********** total visits per month. The video content platform, YouTube.com, was the website with the second highest average monthly visitors, at roughly ********** visits, while Xvideos.com placed third with around ************* visits in the same period.