Apply for a research grant to collect data for your thesis, dissertation, study or an academic paper
Get a 1000$ grant for your research needs
How does it work?
How can I use the grant?
You get up to 1000 US dollars grant that can be used for web scraping services to collect data for academic purposes.
What are the requirements?
To apply for the grant, you should:
- Need to scrape data from the website for your research activities - Use the data exclusively in educational or scientific purposes - Create a 2-4 minute video explaining what data you require, what web scraping service you need and how do you plan to use it in your work.
Who we grant?
Any of the following should apply to you:
- Bachelor or Master student (any major) - Doctorate student - Researcher at an accredited educational institution - High-school students involved in scientific research projects can also apply
What are the eligibility criteria?
We accept research projects on any topic, but we'll have to evaluate if the data collection is technically possible. Our team will also do web scraping legal compliance validation of your project.
Deadline: We select participants each month. All applications received within a calendar month will be processed no later than 10th day of the following month. Note: The grant includes internet scraping service equivalent to $1,000, isn't given out in cash. We give up to 3 grants per calendar month.
How Researchers Use Web Scraping as a Data Collection Technique?
Our world is now digitized, and data has proven to be a useful component for business, entertainment, strategy formulation, and decision making. However, most researchers in diverse fields are at a loss of how to gather and collect data, format it visually, analyze it, and use it to achieve their objectives. Fortunately, web scraping is an effective method through which researchers can collect external data for use in various applications.
Web scraping is a process of collecting and analyzing large data sets to identify trends, patterns, and relationships. It is a powerful tool that researchers can incorporate in their data collection and analytics strategies. The method assists researchers to gather information from different online sources and view it in a central location. Researchers can, therefore, use web scraping as a tool for observing online communities without employing invasive methods.
How it works
The web contains a vast amount of text. The text may be trapped in PDFs, populated from diverse databases, unstructured, or organized in table formats. However, the authors and information owners structure most of the text in XHTML or HTML markup tags that instruct browsers how to display the information. They design and create tags to make text appear in a readable format on the web. Similarly, programmers and vendors develop web scraping tools to interpret the markup tags and follow the programmed instructions on how to collect necessary research data.
The essential stage in a web scraping process is to choose a tool that fits the research needs. The tools include purpose-built libraries within a popular programming language, desktop applications, and manual browser plug-ins. The capabilities and features of web scraping tools vary according to data collection needs and require different learning and time investments.
Web scraping as a data collection method
Researchers can scrape websites for information using various approaches. The most common form includes using software built to scrape vast data amounts from the web automatically. Researchers and businesses use these specialized methods and tools to automate web scraping processes by defining various metrics. They include the specific websites to visit, the information to look for and what data to scrape, and whether to collect data till the end of a page or to repeat the process in other hyperlinks recursively. Furthermore, automated web scraping methods allow researchers to define if a process should capture web data at regular intervals or in real-time to capture data changes.
Web scraping employs two main methods to extract and collect online data. These are web scrapers and web crawlers. Web crawlers use links or keywords that connect websites since they are created using artificial intelligence and programmed to find specific information. On the other hand, web scrapers consist of tools designed to extract relevant information after a web crawler identifies the required data. Researchers can also program the web scrapers to collect and sort web data in various formats to access and alter them offline. Subsequently, researchers can interact with, manipulate, or edit data using file formats, such as .JSON, .CSV, and .XLSX.
Web scraping procedure for researchers
Harvesting extended sizes of data from various internet sources is a common data collection procedure for researchers. Research data typically share four main traits; the data is unstructured, it grows at an exponential rate, it is highly complicated, and it is transformational. The first stage, therefore, is identifying web scraping design depending on the research needs. Numerous free and inexpensive web scraping software tools are accessible for scraping substantial data sets. Some tools analyze the data automatically.
Researchers must then identify relevant websites for scraping data. When collecting a large set of data, researchers can define the population parameters narrowly, which is beneficial as the collected data may include almost all cases of the research phenomenon under study. Collecting a list of such instances permits researchers to use it as a sampling frame (data cases the researcher may choose to include in the research sample).
However, the main challenge in this mode of data collection is deciding the number of pages of the identified websites that should be examined for data, as indicated in the search parameters. The number of hits from a website search depends on the type of the website a researcher is scrapping. For example, large search engines may produce more pages compared to social media platforms. As such, it may be difficult for researchers since scraping data from the same number of pages irrespective of the website may lead to over-representation or under-representation of some sites.
Researchers must then decide the specific content to download from the websites. Discussion boards and blogs usually contain large quantities of discussion posts and accompanying comments, mostly in chronological order. As a result, researchers must decide the exact text they require to download. They can filter the data according to specific topics or date for more detailed information. The lasts stage is scraping the data, which may include transferring the data in readable formats, such as an Excel spreadsheet or word document.
Tools for scraping can be quite different. The significant difference is in the design restriction of the targeted web source. When approaching the creation of the tool, various design factors are to be kept in mind. Moreover, if a non-programmer uses the tool, it should be straightforward yet intuitive, and most importantly, it should return data in a usable form.
Benefits of web scraping for research
1.Access to rich and unique datasets
The internet contains a rich amount of numerical, video, text, and image data. Researchers can collect information on any topic from any of the billions of web pages currently available on the internet. Depending on the research objective, researchers can locate the relevant websites, configure their web crawlers and web scrappers, and collect a custom data set for analysis and analytics. For example, a researcher gathering football information can contain video content by downloading football matches from sites like YouTube, scrape football statistics data from relevant sites, and collect betting data from various bookmakers.
2.Effective data management solution
Rather than copying online data and pasting it to a document, web scraping provides researchers with the freedom to determine the type of data to collect from various websites. As such, collecting research data through web-scraping has higher accuracy compared to other data collection methods. Web scraping also allows researchers to collect data in real-time. There are examples of advanced web crawling and web scraping techniques that store the scraped data in a cloud database to collect data 24/7. Collecting data using automated software programs means that a researcher spends less time copying and pasting internet information directly and mote time on realizing research objectives.
3.It is inexpensive
Most of the web scraping and web crawling tools are available for free, while more advanced ones are available for an affordable price. Researchers can, therefore, collect vast data amounts with better accuracy and lower costs.
4.High speed and low maintenance
An essential aspect usually overlooked when installing new software is the maintenance cost. Long-term maintenance may cause a research budget to exceed the allocated funds. Thankfully, web scraping tools require minimal to zero maintenance for extended usage periods. Web scraping services also enable researchers to collect data with speed. A manual data collection process may take several days while web scraping can perform the same tasks within hours.
Examples of web scraping tools for collecting data
Browser plug-in tools: they allow a researcher to install a web browser plug-in for scraping data in visited web pages.
Programming languages: researchers can use specific libraries in common programming languages for large-scale researches requiring complex web scraping. However, such tools need a detailed up-front learning process to set up and use, despite a tool vendor automating most of the methods.
Desktop applications: downloading and installing web scraping tools on a computer provides researchers with standard interface features and learn various workflows.
Application programming interfaces: a web scraping tool is like an API that allows researchers to interact with text data stored on a website server. Some websites provide specific APIs to enable researchers to gather data.