The massive amounts of data created every day are a boon for academic research that depends on data. Automating the tasks involved in collecting data can make your research process more efficient and repeatable, which can make you more productive. If you’re looking for a way to simplify the process of accessing data for your research, web scraping can help.
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Web archiving is a long-accepted practice of collecting and preserving data from web pages for research. Another, more recent, method of preserving data from web pages involves web scraping. Scraping websites for academic research is an automated process that uses a web-crawling robot, or bot, to extract data from web pages and export it to a usable format like a CSV or JSON file.
If you’re already familiar with web scraping for academic research, feel free to skip around to the sections that interest you most.2
Case Studies for Academic Research Using Scraping
Data scientists already use web scraping extensively to gather data for machine learning and analysis. However, they aren’t the only academic professionals who use web scraping. Other scientists and academics are increasingly relying on web scraping to create a data collection workflow that’s computationally reproducible. In their article in the science journal Nature, Nicholas DeVito, Georgia Richards, and Peter Inglesby describe how they routinely use web scraping to drive their research.
One of their projects involved the use of a web scraper to analyze coroner reports in an effort to prevent future deaths. They searched through over 3,000 reports to find opioid-related deaths. Using a web scraper, they were able to collect the reports and create a spreadsheet to document the cases. The time savings have been tremendous.
Before they implemented the web scraper, they were able to manually screen and save 25 cases per hour. The web scraper was able to screen and save 1,000 cases per hour while they worked on other research tasks. Web scraping also opened up opportunities for collaboration because they can share the database with other researchers. Finally, they’re able to continually update their database as new cases become available for analysis.
Health care research is one of the most common uses for web scraping in academic research. Big data is tremendously useful in determining causes and outcomes in various health care fields. But it’s certainly not the only field that uses web scraping for academic research.
Web scraping has also been useful in academic research on grey literature. Grey literature is literature that’s produced outside of traditional academic and commercial channels. This information is hard to find because it isn’t indexed in any traditional, searchable sources. Instead, it can be reports, research, documents, white papers, plans, and working papers that were meant to be used internally and immediately. Researchers using grey literature are able to increase their transparency and social efficiency by building and sharing protocols that extract search results with web scrapers.
How Scraping Websites for Academic Research Works
Web scraping is the process of gathering data from websites. Although web scraping is usually associated with bots, you can manually scrape data from websites as well. At its simplest, web scraping can involve examining a web page by hand and recording the data you’re interested in in a spreadsheet.
But when most people talk about web scraping, they’re referring to automated web scraping. When you find websites available for scraping school projects or other academic research, using a web scraper will make the process quick and easy. There are several different types of automated web scraping, including:
Almost all web-based text is organized according to HTML markup tags. The tags tell your browser how to display the text. Web scrapers are coded to identify HTML tags to gather the data you tell them to collect. HTML analysis is often used to extract text, links, and emails.
Document object model (DOM) web scrapers read the style of the content and then restructure it into XML documents. You can use DOM parsing when you want an overview of the entire website. DOM parsers can collect HTML tags and then use other tools to scrape based on the tags.
If you’re targeting a specific vertical, a vertical aggregation platform can harvest these data with little or no human intervention. This is usually done by large companies with enormous computing power.
XPath is a query language that’s used to extract data from XML documents. These documents are based on a treelike structure, and XPath is able to use that structure to extract data from specific nodes. XPath is often used with DOM parsing to scrape dynamic websites.
Text Pattern Matching
Text pattern matching uses a search pattern with string matching. This method works because HTML is composed of strings that can be matched to lift data.
As you can see, there are a lot of different factors that go into web scraping. Different methods of scraping need to be matched to use cases and types of websites. If you’re more interested in becoming an expert researcher than an expert in web scraping, you can use a pre-built web scraper like Scraping Robot to simplify the process.
Is Web Scraping for a School Project Alright?
Since web scraping is simply speeding up the process of gathering publicly available data from a website, there are no ethical concerns as long as you use good digital manners, such as not overloading the server. As discussed above, many professional researchers use web scraping to obtain data.
If you’re thinking of using web scraping for school, you should check with your teacher or professor if you have any questions or concerns about web scraping for a particular assignment. Web scraping is legal for a variety of purposes as long as you only scrape publicly available data.
Problems with web scraping
Most websites use anti-bot technology to discourage web scrapers. Websites use anti-bot software to block the IP address associated with bots for several reasons, but not because it’s illegal. Some websites don’t want their competitors benefiting from their data. Others may worry that web scraping will monopolize their server’s resources, which can cause the website to crash.
How to overcome obstacles to web scraping
To get around anti-scraping measures, you’ll need to program your web scraper to appear as human as possible. The biggest advantage to web scraping is how fast it is. Speed is also the surest sign of a bot. If a website detects too many requests sent from the same IP address, it will block that IP address.
There are several ways you can make your web scraper mimic human behavior. First, you’ll need to use proxy IP addresses. A proxy IP address hides your real IP address and makes it look like your request is coming from a different user. Of course, you can’t just use a different IP address and send hundreds of simultaneous requests from that IP address. The website will just block your new IP address.
The solution is to use a rotating pool of proxy IP addresses. Using rotating proxies makes it look like every request you send is coming from a different user. In addition to using rotating proxies, you should schedule your web scraper to issue requests at a slower rate. You don’t have to slow it down to human speeds since you’ll be using proxies. But slowing down your scraper a bit is good digital citizenship, since you don’t want to overwhelm the server you’re scraping.
Finally, space your requests at irregular intervals. Instead of sending requests at perfectly spaced two-second intervals, set your intervals to random spacings. Humans rarely do anything in a perfectly spaced rhythm.
Easy Solutions for Academic Research Using Scraping
If you know how to code, creating a simple web scraper isn’t too hard. But creating a scraper that can do what you want it to do and maintaining all of the moving parts that go along with the scraper is another matter. Scraping Robot handles all of the headaches for you and lets you get on with your research. Web scraping isn’t an efficient solution if you use all of the time you save scraping data to manage your web scraper.
Scraping Robot is a web scraper with various modules pre-programmed for many different scraping purposes. If you have a need for data that can’t be accessed via our existing modules, we can design a module to suit your needs.
When you use Scraping Robot, you’ll get a simple pricing structure based on the number of scrapes you do. There are no subscription fees or complicated tiers to decode. We’ll also handle the headaches for you. For instance, proxies can be extremely complicated. There are different types of proxies, and some of them are more prone to getting banned. If you’re banned, you have to change your proxy IP address. Rotating and managing your proxies can be a pain.
Scraping Robot takes care of proxy management, server management, browser scalability, CAPTCHA solving, and dealing with new anti-scraping measures as they’re rolled out. You can just focus on doing your research, whether it’s for a published paper or a homework assignment, quickly and efficiently. If you run into any problems, our expert support team is available 24/7 to help you out. Reach out today to find out how we can help you with your research with our customizable web scraping solution.
Academic research is just one of the many use cases for web scraping. Web scraping allows professional researchers to build scalable, sharable, reproducible databases they can share with their peers to collect and analyze data. Since being able to reproduce results is foundational to academic research, producing shareable databases adds tremendous value to original research.
While web scrapers are composed of relatively simple code, creating and maintaining them can be time-consuming and laborious. You may collect millions of bits of data before you realize you have a bug and your data is meaningless now. Scraping Robot can help you bypass the hassle so you can focus on scraping websites for academic research.
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