How to Scrape Review Data with Java

March 29, 2021 by Patricia Bennett

Web scraping is one of the best ways to retrieve data accurately and on a large scale. Although Python is great for web scraping, Java is also a viable alternative. Java is a versatile coding language with various libraries for many applications.

#Web scraping with #Java is very straightforward and provides an accurate representation when collecting #data. Click To Tweet

Like Python, a Java web scraper tool uses automation to collect data at a rapid pace, which sure has its advantages over the old copy and paste method of yesteryear.

There are applications where web scraping would be advantageous. For example, those in the financial sector can gather real-time data, and marketing professionals must constantly update trends and buyer personas.

Read on to learn why data scraping is advantageous and what the process entails.

Reasons for Web Scraping

Web scraping is an efficient, quick, and accurate way to process large amounts of data in real-time. Within minutes, you can gather large amounts of data from various relative sources on the web. A company with a web scraper is more competitive, as the data they collect can keep them up to date and current on the latest trends.

Fixing Internal Links

A properly constructed web scraping tool is quick and efficient. It can process large amounts of data in minutes, which would take days to collect manually. It saves time and is far more accurate than other types of data collection. With Java and its various libraries and ease of use, this entire process is quick and efficient.

Who Uses Web Scrapers

Some of the most highly renowned companies – like Google – use web scrapers. Google utilizes the tools for indexing websites and new posts, allowing them to accurately collect the data while automating the entire process.

Because collecting accurate data is critical, digital marketing agencies implement scraping tools as well, allowing them to remain competitive and relevant within their industry. Many agencies will scrape their own data to improve client satisfaction.

A How-To Guide for Web Scraping

Because several libraries are designed to scrape review data with Java, it is one of the best programming languages to gather information.


Below are a few of the libraries available for data scraping.


JSoup is a library that gathers data through DOM or CSS. These open-source libraries are popular for web scraping. These libraries don’t support X-Path parsing, making them beginner-friendly.


This option is an advanced library and often has a learning curve. Businesses often use it to imitate the actions of a user, such as selecting and submitting information. This makes it easier to automate data collection and storage.

HTMLUnit is more advanced than JSoup. It can use X-Path parsing, making testing easier. Many more Java libraries are useful for other applications.


Implementation is quite simple when using Java. In this case, we are going to use the JSoup library as it is beginner-friendly.In the next section, we will go over the dependencies needed to get started using web scraping with Java.

Before implementing Java to your web scraping strategy, you need Java 8, Maven, or any other project management software and a text editor, such as Sublime.

To implement the tool, we need to run this command in Maven:

$ mvn archetype:generate -DgroupId=com.codetriage.scraper -DartifactId=codetriagescraper

-DarchetypeArtifactId=Maven-archetype-quickstart -DinteractiveMode=false

$ cd codetriagescraper

This will help to generate a .xml file that includes our scraper tool. Within the folder created, there will be a “pom.xml” file that will contain all the information related to the project we created and contain the JSoup dependencies.

The next step is to delete the dependencies in the pom.xml file and paste another piece of code. This step updates both the dependencies and the plugin information. To ensure the code works correctly, use this snippet:

$ mvn package

$ Java -jar target/codetriagescraper-1.0-SNAPSHOT.jar

If inputs are correct, you should see “hello world” on the Maven text editor. Now that we’re finished testing, we can now begin assembling our scraper.

It is critical to inspect the website’s HTML before scraping. This will give you the confidence that the correct data is being scraped.

In your browser, right-click the screen and click “inspect.” This will provide you with the HTML and allows you to find the DOM.

When looking at the HTML, look for the line that says “class” and ensure that it has an anchor tag. This is the line that stores the information. We then must open the file and enter this text:

public static void main(String[] args) {

   try {

     // Here we create a document object and use JSoup to fetch the website

     Document doc = Jsoup.connect("").get();

     // With the document fetched, we use JSoup's title() method to fetch the title

     System.out.printf("Title: %s\n", doc.title());

   // In case of any IO errors, we want the messages written to the console

   } catch (IOException e) {




This piece of code can build the scraper and assign the repositories to one page. You can use the repository getElementsByClass() to build the scraper. For each repository, it will include a header with the text “repo-item-title.”

We then run the code and see if the scraper works. It will read “build success” if all the information is correct.

Final Thoughts

Web scrapers are a great way to process large amounts of data that you can use to enhance your business. Ensure the code is correct by testing the scraper. This is why testing is key. By following our methods, you will be able to scrape review data accurately in real-time.

Whether you are a business of finance specialists keeping track of live market data, marketing professionals using data extraction for a strategic edge, or advertisers keeping track of user behavior, web scrapers have become an essential 21st-century tool for fulfilling corporate data needs. Though it may seem like a tedious process, web scraping is the most advanced way to quickly gather large amounts of data and is ideal for many industries.

By collecting and utilizing this data, you can ensure that your business is always up to date with trends, living up to its expectations, and staying a step ahead of the competition.

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