Web Scraping History: The Origins of Web Scraping

Scraping Robot
April 8, 2022
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Web scraping, also known as data harvesting or data crawling, has existed since the beginning of the internet. Although most people now associate web scraping with extracting vast amounts of information from websites, web scraping was created for a completely different purpose — making the World Wide Web easier to use.

Table of Contents

 

Read on to learn more about web scraping history, and use the table of contents to skip ahead if you’d like. We’ll also explore how web scraping has transformed since the late 1980s.

The History of Web Scraping

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Although web scraping sounds like a fresh concept, its history can be dated back to 1989, when Tim Berners-Lee created the World Wide Web.

The World Wide Web and the first website

Berners-Lee created the World Wide Web in 1989 as a way for university professors and researchers to share information. Although it was much less visual and much smaller than today’s internet, it had three important features that web scraping tools still use to this day:

  • Embedded hyperlinks that let users navigate through websites
  • Uniform Resource Locators (URLs) that we still use to assign a scraper to a specific source site
  • Web pages that contain different types of data, such as text, photos, videos, and audio files

Two years after creating the World Wide Web, Berners-Lee created the world’s first web browser. This was an HTTP:// web page that ran on a server on his computer.

The Wanderer

Soon afterward, the first web robot, the World Wide Web Wanderer, was born in 1993.

Created by Matthew Gray at the Massachusetts Institute of Technology, the Wanderer was a Perl-based web crawler that measured the size of the World Wide Web. Later that year, the Wanderer was used to create an index known as the Wandex.

Although the Wanderer had the potential to become a World Wide Web search engine, Gray does not make this claim. It’s also been stated that the Wanderer was never intended to be a search engine.

JumpStation

In 1993, a crawler-based web search engine was born. Known as JumpStation, this bot indexed millions of web pages, turning the internet into an expansive open-source platform the world had never seen before. Before JumpStation, websites relied on human website administrators to collect and edit the links into a readable format.

It was developed by Jonathon Fletcher from Scarborough, England, employed at the University of Stirling in Scotland as a systems administrator. While he was there, he used JumpStation to index 275,000 entries spanning 1,500 servers. Unfortunately, JumpStation was discontinued when Fletcher left the University in late 1994. This was because Fletcher had failed to get any investors to financially back his idea, including the University of Stirling.

In contrast to the Wanderer, JumpStation was quite modern. It used headings and document titles to index web pages found through a simple linear search. Like Google Search, it used an index built by a web robot and searched this index using keywords entered by users. JumpStation also showed its results in the form of URLs that matched the users’ keywords.

Unlike modern web scrapers, however, JumpStation didn’t provide results rankings. It also wasn’t intended to pull massive amounts of data from websites.

BeautifulSoup

In 2004, BeautifulSoup was released.

BeautifulSoup is a library of popular script modules and algorithms that can be used without rewriting. Designed for Python, BeautifulSoup also helps programmers understand site structures and parse the content within HTML containers, saving them from hours of tedious work. It remains one of the most advanced and sophisticated libraries for web scraping.

By this time, the internet had become a much more accessible source of information that anyone with an internet connection could access. As a result, many people started using BeautifulSoup to extract text, pictures, and other information from the web. However, you still needed to know how to code since web scrapers didn’t have visual user interfaces for non-programmers.

The Rise of Visual Web Scrapers

how to rise visual web scraping

A few years after BeautifulSoup’s release, modern web scraping was born.

Several companies launched visual web scraping software platforms that allowed users to manually highlight the information they wanted to extract and extract it into an Excel spreadsheet or database. These programs had simple user interfaces, allowing non-programmers to pull data from the web easily.

Instead of inputting commands in Python, Ruby, and other programming languages, all you have to do is:

  1. Select elements to extract.
  2. Select the extraction sequence — for instance, extracting JPEG files before text.
  3. Press the “Extract” or “Start” button to start the scraping process. The visual web scraper will automatically populate the selected Excel spreadsheet or database with the scraped data.

Visual web scrapers vary greatly regarding flexibility, usability, price, extra features, and the extent to which they help you spot and debug scraping problems. Although there are some free open-source visual web scrapers, most require you to pay hefty subscription fees for their services. They may also:

  • Make it difficult for you to export scraped data to certain types of databases
  • Require you to download other apps and programs to scrape certain kinds of websites, such as dynamic webpages
  • Require you to build separate parsers for handling metadata

That’s where Scraping Robot comes in. Unlike most visual scrapers, Scraping Robot lets you scrape directly from every type of website without downloading other apps and programs. It also parses metadata to return the data you want, so you don’t have to build separate parsers for handling metadata. Scraping Robot also offers frequent improvement and module updates and the ability to request new modules and features.

The Rise of Web Scraping For Small Businesses

web scraping for small business

Thanks to the meteoric rise of web scraping, many small businesses have taken to web scraping like bees to honey. This is because web scraping provides many advantages for small businesses, including:

Replacing manual data extraction

Visual web scrapers can do everything a human scraper can, only better, faster, and cheaper.

Compared to human scrapers, scraping bots can extract data from thousands of pages per hour, which means that humans can never compete with them. Scraping bots can also be set to run without breaks and start and stop at various times of the day. This means that you can save a lot of money by getting a data scraping bot.

Monitoring competitors

Web scraping can also help you stay on top of your competitors. Here’s what you can monitor with a web scraper:

  • Competitor prices and price changes
  • Competitor reviews to identify strengths and weaknesses in your competitor’s marketing strategy and offerings
  • New products that competitors have added to their stores
  • Products that competitors have retired from their stores
  • Industry trends, such as, “What is the most popular headset in Spring 2022?”

Monitoring public opinions

Data scraping can give you a clear picture of what the public thinks about your brand, what influences their opinions, and how their views have changed over time. You can pinpoint how different demographics feel about a particular product, marketing strategy, or service by scraping online communities, forums, boards, and your competitors’ review sites. This rich information can help you develop and adjust products, business strategies, and marketing campaigns.

Making future predictions

Web scraping can also help you make predictions by gathering historical information in a readable format for further analysis and testing. You can then use advanced analytics techniques like predictive analytics and machine learning to predict future outcomes.

Many Human Resources (HR) departments use predictive analytics on scraped datasets to predict how employees will act in the future.

Increasing outreach

Finally, data scraping can boost your outreach and SEO. By scraping competitors’ sites for keywords and links, you can build stronger links and make more connections in your industry.

For instance, let’s say you want to sell more gaming headphones. You can use a web scraper to collect all of your competitors’ keywords and links to attract leads to their websites. You can then add the hottest keywords and links to your product pages and blogs to get more leads.

Start Scraping With Scraping Robot

start scraping with scraping robot

As you can see, web scraping history is a long and interesting tale. Although we currently associate it with the efficient extraction of data from the internet, web scraping was initially meant as a way to navigate the internet. Web scraping only became a way to gather massive amounts of information from the net when visual scrapers like Scraping Robot were created in the 2000s.

Unlike the web scrapers of the 90s, Scraping Robot is incredibly user-friendly and doesn’t require coding knowledge. All you have to do is select elements to extract, determine the extraction sequence, and start the scraping process. You’ll get a fully populated Excel or spreadsheet with all of your scraped data in just a few seconds.

What’s more, you don’t have to pay to get started. By registering an account with Scraping Robot, you’ll automatically get 5,000 free scrapes per month.

Interested? Get started with a free Scraping Robot account today.

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