Web design service companies have experienced significant growth over the past few years, driven by the expanding use of the Internet. As online operations have become more widespread, businesses and consumers have increasingly recognized the importance of maintaining an online presence, leading to robust demand for web design services and boosting the industry’s profit. The rise in broadband connections and online business activities further spotlight this trend, making web design a vital component of modern commerce and communication. This solid foundation suggests the industry has been thriving despite facing some economic turbulence related to global events and shifting financial climates. Over the past few years, web design companies have navigated a dynamic landscape marked by both opportunities and challenges. Strong economic conditions have typically favored the industry, with rising disposable incomes and low unemployment rates encouraging both consumers and businesses to invest in professional web design. Despite this, the sector also faced hurdles such as high inflation, which made cost increases necessary and pushed some customers towards cheaper substitutes such as website templates and in-house production, causing a slump in revenue in 2022. Despite these obstacles, the industry has demonstrated resilience against rising interest rates and economic uncertainties by focusing on enhancing user experience and accessibility. Overall, revenue for web design service companies is anticipated to rise at a CAGR of 2.2% during the current period, reaching $43.5 billion in 2024. This includes a 2.2% jump in revenue in that year. Looking ahead, web design companies will continue to do well, as the strong performance of the US economy will likely support ongoing demand for web design services, bolstered by higher consumer spending and increased corporate profit. On top of this, government investment, especially at the state and local levels, will provide further revenue streams as public agencies seek to upgrade their web presence. Innovation remains key, with a particular emphasis on designing for mobile devices as more activities shift to on-the-go platforms. Companies that can effectively adapt to these trends and invest in new technologies will likely capture a significant market share, fostering an environment where entry remains feasible yet competitive. Overall, revenue for web design service providers is forecast to swell at a CAGR of 1.9% during the outlook period, reaching $47.7 billion in 2029.

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.

The internet service providers industry uses wired infrastructure to provide clients with internet access and related services, like web hosting, web page designing and consulting related to internet connectivity. Rising internet usage has benefited industry revenue growth, and government-subsidized network expansion has done the same, increasing the number of US broadband connections. A push toward broadband expansion in rural markets and a climb in demand from business customers has boosted industry revenue, which is poised to incline at an annualized rate of 3.5% to $168.5 billion in 2025, including growth of 4.2% in 2025 as investments and activity mount in line with an improving macroeconomic environment. As households increasingly rely on the internet for streaming, gaming, remote work, and cloud computing, ISPs are scrambling to deliver faster and more reliable service. The rising adoption of cloud computing, which involves accessing data online, has boosted demand for dedicated internet access services sold at a higher profit. With increasing demand, providers have begun launching fiber optic networks, rapidly improving connection speeds. Major enterprises that typically benefit from economies of scale also continue to bundle TV and phone, which includes Voice over Internet Protocol services and high-speed internet into one service package, adopting new technology. Consolidation has swept the industry, with blockbuster mergers—such as T-Mobile’s tie-up with Sprint and Verizon’s multi-billion-dollar acquisition push—reshaping market share and intensifying competition. At the same time, average broadband speeds have more than doubled, but ISPs have faced mounting pressure from cord-cutters, OTT competitors and fierce price wars, often leading to flat or declining revenues per user even as consumer bandwidth use reaches new heights. This competitive environment has led to plummeting profit. Looking ahead, the ISP industry shows no sign of slowing down. Over the next five years, fiber expansion and 5G fixed wireless will reach an even greater share of US households. Providers will continue investing heavily in gigabit networks, edge computing and advanced Wi-Fi to keep pace with the explosion in cloud computing, IoT devices and remote work. Retaining customers will hinge on delivering faster speeds, greater reliability, strong security and innovative value-added services, especially as open-access networks and new entrants threaten to erode traditional market advantages. Continued demand will lead to industry revenue growth, poised to climb at an annualized rate of 4.4% to $208.9 billion in 2030.

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.

🍷 FineWeb

15 trillion tokens of the finest data the 🌐 web has to offer

  What is it?

The 🍷 FineWeb dataset consists of more than 15T tokens of cleaned and deduplicated english web data from CommonCrawl. The data processing pipeline is optimized for LLM performance and ran on the 🏭 datatrove library, our large scale data processing library. 🍷 FineWeb was originally meant to be a fully open replication of 🦅 RefinedWeb, with a release of the full dataset under… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb.