In our ever-evolving way of life with technology, we can access several pieces of data in a short amount of time. When writing a research paper, gathering data and information is much easier than it was decades before.
However, with so much data available online, many people may show concern over web scrapers browsing websites to copy and store data on their computers. Many of these websites incorporate technical measures to keep scrapers from accessing their webpages, which may inconvenience others.
As data ethics and web scraping clash, many resources developed ways on how to prevent getting blacklisted while scraping.
The Power of Data
Data collection has earned a very poor reputation in recent years, following the likes of the 2018 Facebook data breach. However, this should never overshadow the fact data collection has been and still remains a critical driver for the Fourth Industrial Revolution’s success.
Furthermore, not all data collection is a product of scraping: humans have been collecting data for millenia. This ranges from oral histories, and paper-based surveys to productivity tools that track employee activity and websites cookies. Data directs our everyday lives and empowers us as a species to make fact-based decisions.
The Foundations of Data Ethics
Data ethics refers to the ways sensitive data is shared, maintained, analyzed, and appropriated. People also associate data ethics with evaluating moral problems related to data, algorithms, and corresponding practices for morally acceptable solutions.
Other aspects that play a role in data ethics include the transparency of how available data is used, why it is being collected, how long they will keep or use it, and the possibilities of how the data can be altered or amended.
Several principles play a role in how the data is accessed and used on multiple platforms. By incorporating these, people determine how to showcase the data that others may come across.
Ownership
Typically, data ownership refers to an individual’s ability to possess and control the information they have. When someone holds ownership over their data, they have the privilege of creating, accessing, modifying, selling, and removing it, among other responsibilities.
Data owners also hold the right to give others access to the privileges they uphold. While these factors may vary between companies or individual owners, they dictate the rights of how their data is shared, who can access it, and how others can use it.
Consent
If an outside party wants to collect data, it would be best to establish consent with their potential participants. For example, suppose a group of people were to participate in an online survey for research purposes. In that case, the people heading it should ask them for consent before inputting their personal information.
Ideally, asking for their consent is better than inferring it without notification. In specific scenarios, data collectors can protect their participants’ identities and data through confidentiality and anonymization.
Privacy vs. Openness
An ongoing argument relevant to data ethics is keeping specific online data types private or open to the public. While some may argue about privacy breaching via the algorithms resulting from their online browsing, some may argue data should be available and have minimal restrictions.
Privacy risks may factor from AI algorithms sprouting out without businesses implementing regulations for storing and taking data or information from countless sources.
Reasons People Might Oppose Web Scraping
Due to the vast abundance of online data, some people may find web scraping to be unethical. A valid question remains in several peoples’ minds: is web scraping legal?
While web scraping is not an inherently bad thing, its misuse depends on the context of how someone uses it. Several people believe there are risks to having personal data open online for unethical web scrapers to take, use, or abuse, while others believe web scraping may overload or damage web servers and sites.
If individuals do not follow a website’s terms of use policies, their web scraping may be in violation of it.
Identity Theft
Several social media websites may ask for personal data when people register for an account. This data may include phone numbers, email addresses, and other personal information such as home addresses or a social security number.
People are more susceptible to leaving their information public for scams and violations of their private information. In some cases, scrapers may also obtain trade secrets.
Plagiarism
Although people follow several citation rules when borrowing factual data or information, scrapers taking the data and claiming it as their own is an unethical breach of copyright infringement. A simple copy and paste account for stealing content and using it without acknowledging its source is plagiarism.
For example, suppose a student takes a section of a research article and paste it into a report without citing its sources. In that case, they disregard the original material and publish it as theirs.
Nowadays, several websites and applications allow users to paste text or data and track the differences between plagiarized and original content. With this technology, people find new ways to combat plagiarism contributed to web scraping for illegal purposes.
Spam Creation
When spammers get a hold of someone’s contact information, such as an email address or mobile number, that person is more likely to find unwanted messages for suspicious services. Outside parties typically send these messages in bulk and target users with promotional emails and ads.
Web scraping also collects phone numbers in bulk to target people by posing as insurance companies, recruiting services, tax fraud notifications, or student loan repayment services, among other businesses.
Fundamentals of Web Scraping
While several people use web scraping for malicious intent, others can still engage in ethical web scraping when done responsibly. Web scraping typically involves web analysis, data crawling, and data organization.
Several individuals and companies may use web scraping for several practical situations, including data analysis for eCommerce or healthcare, research and development to improve products, and helping businesses thrive by doing market analysis and price comparisons to others in their industry.
Due to some websites implementing strict policies against harmful web scrapers, those who do it without malicious intent get blocked from the site without a chance. To avoid this inconvenience,
Typically, a person has to know web technology and programming languages, such as Python, to perform web scraping without much trouble.
Ways to Avoid Blacklisting While Web Scraping
Some websites may integrate methods to block scrapers’ IP addresses to keep them from violating their terms of use through unethical web scraping. This strategy is typically ideal for keeping competing companies from stealing information to use for their objectives.
If a person happens to get blocked by websites, there are several ways to counteract getting blacklisted by the websites they browse.
Some people switch their IP addresses using proxy servers or VPN services to swap them out and access sites that block them through their original ones. Others may opt for reducing their page browsing speed to avoid getting blocked as an automated crawler.
Another tool scrapers may use to overcome blacklisting is CAPTCHA-solving services to automatically fill them out as they parse a webpage’s coding.
If the website a person uses has general terms and conditions on web scraping for the public, it would be best to check those out before web scraping. By understanding what is permitted and what is not, web scrapers can reduce their chances of getting blacklisted on a website.
Using Programs for Web Scraping
Several programming and scripting language tools exist to assist with web scraping, such as Ruby. It uses two primary frameworks or libraries to help users scrape several different types of websites. Although they perform similar tasks, they do have a few differences in how they function.
While accessing a webpage, scrapers and parsers can right-click anywhere and select the “Inspect Element” prompt. This process works for bodies of text, videos, pictures, and other graphics the page has. Once they find the data they want to save, they can process it for storage.
Nokogiri
Nokogiri utilizes CSS and Xpath selectors to parse website data. Typically, it is a tool used for parsing HTML and XML and creating new objects from them. By extracting HTML, scrapers can take a webpage’s data and save its essential parts as readable text for safekeeping. Most people store this data in CSV files.
Kimurai
Kimurai is compatible with PhantomJS and other headless browsers. While scrapers can use this framework to parse HTML sites, it is an ideal tool for scraping websites crafted with Javascript.
It can scrape and process several web pages simultaneously for those who prefer saving time to extract the data they need. It also stores the extracted data in one place for processing.
Conclusion
Despite the controversies that web scraping has concerning data ethics, there are still ethical ways to use this process without causing harm. The abundance of data across the internet makes it susceptible for people to copy and republish as their own.
As long as scrapers follow specific guidelines on websites and give credit to sources they acquired the data from, their actions will not automatically be considered unethical. While some may argue about how web scraping normalizes plagiarism and identity theft of public and private data, others state gathering data is crucial for advancement and business growth.
There are several ways to prevent getting blacklisted while scraping, from slowing down their activity while browsing to switching their proxy servers to override blocking. Several tools are available for web scraping web pages made with several programming languages. Depending on what a scraper wants, they can also perform these tasks for multiple pages at a time.
As technology grows and adapts, the reputation of manual and automatic web scraping depends on who does it and how they use the data.
