The Origin of Web Scraping

The origins of Scraping can be traced back to the beginning of the World Wide Web (Internet) when there was no search function. Before search engines(google) were developed, the Internet was simply a collection of File Transfer Protocol (FTP) sites where users could search to find specific shared files.

With the rapid growth of the Internet, an automated program known as a web scraper was created to find and combine the distributed data available on the Internet. It could explore all of the websites on the Internet and then copy them into a database to form an index.

As the resources on the web become increasingly rich but cluttered, the cost of accessing information becomes higher. Accordingly, web scraping has evolved to become smarter and more applicable. It can be said that the emergence and development of web scraping have enabled us to search for the information we want on the Internet and have greatly improved the efficiency of web search.

What is Web Scraping?

Web Scraping (also called web data extraction or data scraping) refers to fetching large amounts of data from websites through automated methods. It works like a probing machine, whose basic operation is to simulate human behavior by skulking around websites, clicking buttons, checking data, or memorizing the information it sees. Web scraping can replace humans to automate browsing information on the Internet and collect and organize data.

Many companies collect external data and support their business operations by web scraping, which is a common practice today in several areas.

What Kind of Web Scraping is There?

Web Scraping can be mainly classified into Web-wide Scraping, Subject Web Scraping, Incremental Web Scraping, deep web Scraping and other types according to the implemented techniques and structures. However, the actual web scraping is generally a combination of these sorts due to the complex internet environment.

• Web-Wide Scraping

Web-wide Scraping, as the name implies, scraps the target resources on the whole Internet, so the amount of data scraped is massive,, and the scope of scraping is also very large. Web-wide Scraping generally adopts certain scraping strategies, which are mainly divided into depth-first scraping strategy and breadth-first scraping strategy. Web-wide raping is mainly used in large search engines and has very high application value for enterprises.

• Subject Web Scraping

Subject Web Scraping means that selectively crawls web pages according to a padoptsined theme. It's mainly applied to scraping specific information and mainly for a specific class of people.

Subject Web Scraping also consists of an initial URL collection, URL queue, page crawling module, page analysis module, page database, link filtering module, the content evaluation module, link evaluation module, etc. Among them, the content and link evaluation module scraping specific information and the importance of links and content.

There are four main strategies for Subject Web Scraping, content-based evaluation, link-based evaluation, augmented learning, and contextual graph-based. Subject Web Scraping can save a lot of server resources and broadband resources in the actual application process since it has highly practical that crawls purposefully by corresponding topics.

• Incremental Web Scraping

"Incremental" here corresponds to "incremental update" which means only the changed areas are updated, while the unchanged areas are not updated.

Incremental web scraping, when scraping web pages, only scrap pages with changed content or newly rated pages, and do not crawls pages with unchanged content. Incremental Web scraping can, to a certain extent, ensure that the pages scraped are as new as possible.

• Deep Web Scraping

Web pages can be categorized into surface pages and deep pages by the way they exist. A surface page is a static page that can be reached by using a static link without submitting a form, while a deep page is a page that can be obtained only after submitting certain keywords. The deep page numbers are sometimes far more than the surface pages on the Internet.

Deep web scraping can scrap deep pages of the Internet, and to scrap deep pages, in the meantime, they need to find a way to fill in the corresponding forms automatically. The deep web scraper is mainly composed of URL list, LVS list (LVS refers to the tag/value set, i.e. the data source that fills the form), scrap controller, parser, LVS controller, form parser, form processor, response parser, and other parts.

What are Web Scraping Used For?

We’ve put some of the most common ones below.

For cyber users, search engines: convenience for web users by scraping sites

The fact is that each of us is enjoying the benefits of scraping for free every day. Nowadays, with the rapid development of the Internet, we can see information from numerous websites all over the world in any search engine. For example, Google will scrap through the vast amount of Internet information every day, scraping for quality information and included. When the user retrieves the corresponding keywords on the google search engine, Google will analyze the keywords, find out the relevant pages from the included pages, sort the results according to certain ranking rules and finally show the results to the user.

For companies, efficient access to valuable information

Data scraping can be a powerful tool for staying ahead of the competition in business. For example, suppose a company invests money in promotions for its products to generate sales but is unaware that competitors are one step ahead of them through the use of business automation technology and web scraping. web scraping can quickly identify a competitor's new pricing shortly after it goes live, allowing competitive business leaders to respond quickly.

In the modern business world, instant information updates and the ability to intelligently respond to new situations and seize opportunities allow companies to stay ahead of the competition at all times. Business leaders and managers can rely on business automation technology to provide them with clear, organized data to take into account when making critical decisions. Here are some of the leading use cases:

• Price research:

Companies can use web scraping to scrape price data on competitive products as a way to help inform their own company's decision-making and reference in their pricing strategy. Also, setting an optimal price setting based on competitor prices can help a company get better results in a subsequent competition.

• New potential customers:

The companies can see the data information of new users on the website or app platform by web scraping, including the source, login country, stay page, stay time, login email and other valuable information, which can help companies to get potential customer leads efficiently.

• Consumer sentiment analysis:

Understand the constantly changing whims, opinions, and buying tendencies of your target audience regarding your brand, perform ad verification as well as brand protection.

• Market research:

For market research by corporations, web scraping can be utilized. High-end web scrap data gathered in big numbers can enable firms to analyze consumer patterns and determine the strategies to be taken by the company in the future.

However, it's important to note that web scraping can also have negative consequences for businesses， including intellectual property theft, data privacy violations, website performance issues, and the misuse of data. It is important for businesses to take steps to protect themselves from web scraping and to use it ethically and responsibly.

How GeeTest Protects Businesses from Web Scraping?

Web scraping, the practice of automatically extracting data from websites, has become increasingly common in recent years. While it has many legitimate uses, it can also be used for malicious purposes, such as stealing intellectual property, sensitive information, and other valuable data. This is why businesses need to protect themselves from web scraping, and this is where GeeTest comes in.

• Advanced Bot Detection

Unlike other vendors, GeeTest has been committed to pushing for technological self-sufficiency, which is what imitators can never surpass for ten years. GeeTest's advanced bot detection technology can accurately distinguish between human users and bots. By analyzing user behavior, such as mouse movements and click patterns, GeeTest can detect most bots and scrapers. This helps protect businesses from data theft, content theft, and other forms of web scraping.

• Flexible Risk Management

Customizable Risk Policies: GeeTest allows businesses to create their own risk policies, giving them greater control over the types of threats. This means that businesses can tailor their risk management strategies to their specific needs, rather than relying on a one-size-fits-all approach.

• Customizable Dashboard: Real-time Risk Assessment

GeeTest's bot management solutions provide real-time analysis of user behavior, which supports visualized traffic analysis and custom security settings, helping you better understand the attack trend in your business. GeeTest's real-time risk assessment system allows businesses to quickly detect and respond to threats as they occur.

In conclusion, web scraping can pose a significant threat to businesses, but GeeTest's advanced bot detection and authentication solutions can help businesses defend against it. By providing advanced bot detection solutions, GeeTest ensures that only real users can access a website or web application. This effectively blocks most bots and scrapers, which helps protect a company's intellectual property, sensitive data, and revenue streams. Furthermore, GeeTest's solutions are highly customizable and can be tailored to fit the specific needs of any business, making it an ideal choice for businesses of all sizes and industries looking to defend against web scraping.