Web scraping is one of the more controversial online practices. It has sparked numerous discussions, both on ordinary and political levels. One of the biggest privacy scandals of the previous decade – Cambridge Analytica – involved harvesting more than fifty million Facebook user profiles.
Simultaneously, HiQ’s web scraping company won a CFAA lawsuit against LinkedIn regarding their open profiles. How could these two relatively similar cases have directly opposite outcomes? The answer lies within the concept of privacy and personally identifiable information (PII).
Cambridge Analytica’s case involves gathering excessive amounts of PII for psychological manipulation. Meanwhile, HiQ practices involve business-related professional information to enhance business operations. To put it short, not all data scraping is the same. Using this technology may bring significant benefits or damage your reputation. It depends on the way you use it.
The Benefits of Web Scraping
Web scraping is primarily very simple. You’re scraping data when you go to a website, copy its relevant information to a file, and repeat it on another site. A person comparing different commodity prices on various retail sites is scraping data. Nothing wrong with that. Comparing prices is beneficial because it saves money and allows picking the best service without overpaying.
On a large scale, the same applies to businesses. It’s a way to deal with Big Data. Unlike casual Internet users, businesses have to deal with thousands and millions of data units. Of course, they could hire additional staff for manual labor. However, achieving the same results with automated processes saves both time and money. Moreover, technologically adept businesses can build unique data scrapers to adhere to their needs and remain strictly within legal and ethical boundaries.
Most businesses successfully implement transparent web scraping techniques. Alongside saving time and human resources, it contributes to data accessibility and organization. Big Data is here to stay. After all, Big Data is used in crucial public spheres like healthcare, public transportation, agriculture, education, etc. But how do you manage vast amounts of data?
Professional data scrapers return data in a machine-readable format, which can automatically be used with other software for analysis. Nowadays, most data aggregation is done via powerful computers. Once you receive publicly available relevant online data in an organized file, you can immediately proceed with the next step. Moreover, you can customize the format and structure of the dataset, making it compatible with various software.
Web scraping excels at data accuracy. Gathering it manually always involves human error and is susceptible to change. For example, analyzing Amazon’s prices manually would take too much time and exhaust the employee (increasing the chances of a mistake), only to realize the prices have changed and the data is useless. Web scraper can continuously monitor selected and available data sectors and trace changes. It makes them an invaluable tool for price comparison.
Lastly, web scraping is inexpensive. It has a learning curve, but once you warm up to the technology, you will carry out tasks for free that would otherwise cost a professional programmer a monthly salary. What’s more, once you learn to create and use data scrapers, you can customize them for different tasks. You do not have to start anew with every new data analysis. With time, your web scraping experience will pay out severalfold.
The Risks of Data Scraping
The risks of data scraping primarily stem from the lack of knowledge or ill intent. Firstly, you need to be aware of copyrighted material. If something is publicly available, it doesn’t mean you can use it. Usually, it includes articles, designs, videos, etc. In other words, you can’t benefit from other people’s creative work without their consent.
Then there’s PII. There’s an obvious difference between LinkedIn and Facebook profiles. People use the former knowing their information will be scrutinized. Meanwhile, the latter holds much sensitive information not to be shared among third parties. Even though the Facebook account may be public, it doesn’t provide an ethical basis to scrape its information. Due to (so far) the lack of governmental regulations, it might not be against the law. But if you get caught, damage to your reputation will be devastating and irreversible.
The risks of data scraping don’t stop with the ethical line. Your web scraper connects to online websites and sends them requests. You may overload the websites if you don’t manage your end correctly. The website owners will be displeased. Also, you cannot scrape data from services that require logging in. Websites with strict ToS need to be accepted by actual users, not automatization software. Bypassing ToS for data gathering is unlawful activity.
Conclusion
To summarize, web scraping is a progressive technology. It can be used both for good and bad. If you’re unsure whether you can scrape one website or another, don’t hesitate to contact their administrators. Some websites even provide APIs for legal data gathering. Furthermore, avoid gathering private personal information at all costs and stick to business-relevant data.
