A guide to data scraping

  • 16/05/2020

Data Scraping, in its most common form, refers to a technique in which a computer program extracts data generated by another program or computer.

Data collection, more often than not, manifests itself in the data extraction process on the Web, the process of using an application to extract valuable information from a website like the Google search engine itself.

In general, companies do not want their exclusive content to be downloaded and reused for unauthorized purposes. As a result, they do not expose all data through an API (Application Program Interface) or another easily accessible resource.

Scrapers, on the other hand, are interested in obtaining data from the website, regardless of any attempt to limit access. As a result, there is a game of cat and mouse between Web data Scraping and various content protection strategies, with each trying to outdo the other.

The process of extracting the Web is quite simple, although the implementation can be complex. Web capture takes place in 3 steps:

First, the piece of code used to extract the information, which we call a scraper, sends an HTTP GET request to a specific website.

When the site responds, the Scraper analyzes the HTML document for a specific data pattern.

After the data is extracted, it is converted to any specific format created by the Scraper author.

Scrapers can be designed for several purposes, such as:

Content collection

  • the content can be removed from the website in order to replicate the unique advantage of a particular product or service that depends on the content. As an example, a product like the Yelp website depends on reviews; a competitor can collect all of the Yelp review content and play the content on their own website, pretending that the content is original.

Price capture

  • by collecting price data, competitors can aggregate information about their competition. This can allow them to form a unique advantage.

Contact Scraping / Capture

  • many web sites contain plain text email addresses and phone numbers. By capturing locations such as an online employee directory, a Scraper can aggregate contact details for mailing lists, robot calls (bot) or malicious attempts at social engineering. This is one of the main methods used by spammers and scammers to find new targets.

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