Job Board Scraping

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A Complete Guide to Web Scraping Job Postings | Octoparse

The online job market has undoubtedly overridden in-person hiring activities. This is especially true when most cities around the globe face rounds of lock-down and more jobs shift to a remote mode since the 2020 covid outbreak. In this sense, web scraping job postings serve not only institutions and organizations but also individual job seekers.
Contents of the Guide on Job Scraping
What’s job scraping
How job data is used
Job scraping challenges
Options for job scraping
Final words
What’s Job Scraping?
Job scraping is to gather job posting information online in a programmatic manner. This automated way of extracting data from the web helps people get jobs data efficiently and build a resourceful job database by integrating various data sources into one. Job scraping is the use case of web scraping in the job area and job data parsing, analyzing, and managing may come after the extraction process is done.
Where to fetch job data? Company’s career pages, giant big boards like Monster, Glassdoor, or Indeed, personal job aggregator websites, and job portals serving all sorts of niche markets are the important sources for people who are applying job scraping. From all these sources, job scraping can easily get you information such as job title, job description, location and compensation.
How Job Scraping Data Is Used?
According to the report made by Gallup far back in 2017, 51% of employees keep an eye on new opportunities online and 58% of job seekers look for jobs online. In recent years, social media recruiting has become an essential way to seek quality hires as well.
These needs for online recruiting resources give rise to the business of job boards and job aggregator websites. This kind of aggregator website is really making money.
Job Data Uses in Practice
Fueling job aggregator sites with fresh job data.
Collecting data for analyzing job trends and the labor market.
Tracking competitors’ open positions and compensations to get yourself a leg up in the competition.
Finding leads by pitching your service to companies that are hiring for the same.
Staffing agencies scrape job boards to keep their job databases up to date.
And trust me, these are only the tip of an iceberg, job data create values in more unexpected ways.
Challenges for scraping job postings
Although job scraping can be extremely helpful in these respects, challenges that lie in the journey may frustrate many.
Gathering Job Data from Multiple Sources
First and foremost, you’ll need to decide where to extract this information. There are two main types of sources for job data:
Major job aggregator sites like Indeed, Monster, Naukri, ZipRecruiter, Glassdoor, Craiglist, LinkedIn, SimplyHired,, Jobster, Dice, Facebook jobs, and etc.
Every company, big or small, has a career section on their websites. Scraping those pages on a regular basis can give you the most updated list of job openings.
Niche recruiting platforms if you are looking for jobs in a certain niche, like jobs for the disabled, jobs in the green industry, etc.
Anti-scraping Techniques That Block Job Scraping
Next, you’ll need a web scraper for any of the websites mentioned above.
Large job portals can be extremely tricky to scrape because they will almost always implement anti-scraping techniques to prevent scraping bots from collecting information off of them. Some of the more common blocks include IP blocks, tracking for suspicious browsing activities, honeypot traps, or using Captcha to prevent excessive page visits.
Well, there are still ways to bypass anti-scraping techniques and straighten the thing out.
High Cost for Job Crawlers Building and Maintenance
On the contrary, the company’s career sections are usually easier to scrape. Yet, as each company has its own web interface/website, it requires setting up a crawler for each company separately. Such that, not only the upfront cost is high but it is also challenging to maintain the crawlers as websites undergo changes quite often.
For job board builders, difficulties in the data scraping would be even more.
What are the options for job scraping?
There are a few options for how you can scrape job listings from the web.
1. Hiring a web scraping service (Daas)
These companies provide what is generally known as “managed service”. Some well-known web scraping vendors are Scrapinghub, Datahen, Data Hero and etc. They will take your requests in and set up whatever is needed to get the job done, such as the scripts, the servers, the IP proxies, etc.
Data will be provided to you in the format and at the frequency required. The charge is based on the number of websites, the amount of data, and the frequency of the crawl. Some companies charge additional for the number of data fields and data storage.
Website complexity is, of course, a major factor that could have affected the final price. For every website setup, there’s usually a once-off setup fee and monthly maintenance fee.
Data As a Service (Daas)
Pros:
No learning curve. Data is delivered to you directly.
Highly customizable and tailored to your needs.
Cons:
High costs ($350 ~ $2500 per project + $60 ~ $500 monthly maintenance fee).
Long term maintenance costs can cause the budget to spiral out of control
Much time is needed in communication and development (3 to 10 business days per site).
2. In-house web scraping setup
Doing web scraping in-house with your own tech team and resources comes with its perks and downfalls.
Web scraping is a niche process that requires a high level of technical skills, especially if you need to scrape from some of the more popular websites or if you need to extract a large amount of data on a regular basis. Starting from scratch is tough even if you hire professionals, these development guys are expected to be well experienced with tackling the unanticipated obstacles.
Owning the crawling process also means you’ll have to get the servers for running the scripts, data storage, and transfer. There’s also a good chance you’ll need a proxy service provider and a third-party Captcha solver. The process of getting all of these in place and maintaining them on a daily basis can be extremely tiring and inefficient.
What’s more, the issue of legality shall be considered. Generally speaking, public information is safe to scrape and if you want to be more cautious about it, check and avoid infringing the TOS (terms of service) of the website. Hiring a professional service provider will surely reduce the level of risk associated with it.
In-house Web Scraping Team
Complete control over the crawling process.
Fewer communication challenges, faster turnaround.
High cost. A troop of tech costs a lot.
Difficulties in hiring.
Infrastructure requirements.
Maintenance headache. Scripts need to be updated or even rewritten all the time as they will break whenever websites update layouts or codes.
Legal risks.
3. Using a web scraping tool
Technologies’s been advancing and just like anything else, web scraping can now be automated.
There are many helpful web scraping software that is designed for non-technical people to fetch data from the web. These so-called web scrapers or web extractors transverse the website and capture the designated data by deciphering the HTML structure of the webpage. Most web scraping tools support monthly payments ($60 ~ $200 per month) and some even offer free plans that are quite robust.
You’ll get to “tell” the scraper what you need through “drags” and “clicks”. The program learns about what you need through its built-in algorithm and performs the scraping automatically. Most scraping tools can be scheduled for regular extraction and can be integrated to your own system.
Web Scraping Tool Application
Budget-friendly.
Non-coder friendly.
Scalable. Easily supports projects of all sizes, from one to thousands of websites.
Fast turnaround.
Complete control in the data extraction.
Low maintenance cost.
Learning curve. Depending on the product you choose, Octoparse is rather easy to use.
Compatibility. There’s never going to be 100% compatibility when you try to apply one tool to literally millions of websites.
Captcha. Some web scraping tools cannot solve Captcha.
To sum up, there’s surely going to be pros and cons with any one of the options you choose. The right approach should be one that fits your specific requirements (timeline, budget, project size, etc). Obviously, a solution that works well for businesses of the Fortune 500 may not work for a college student. That said, weigh in on all the pros and cons of the various options, and most importantly, fully test the solution before committing to one.
Artículo en español: Una guía completa para las publicaciones de trabajos de web scrapingTambién puede leer artículos de web scraping en El Website Oficial
Job Scraping: How to scrape job postings from a company’s job board
How to Build a Profitable Job Aggregator
A Complete Guide to Web Scraping Job Postings
Tutorial: Scrape job data from Glassdoor
Tutorial: Scrape job information from indeed
hiQ vs. LinkedIn ⁠— It Is Legal to Scrape Publicly Available Data

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hiQ vs. LinkedIn ⁠— It Is Legal to Scrape Publicly Available Data

Stairway to heaven, If you’re in the business of web scraping, that is.
It is legal to scrape publicly available data. There is a massive amount of data available in the public domain of the web. However, when it comes to the utilization of the same, little has been done to date. But today, service companies are providing data as a service, or building solutions that are backed by data. Say you want to know the prices of 20000 items across 5 different websites, some services can help you with that. Be it hiring recruits, or deciding what price would be right to list your house at, web scraping helps with all. However, even though web-scraping usually involves companies scraping data from the open Internet, many companies are opposed to this. Why? They claim data from the users as their own. And apparently, they are the only one who has any right to it. A big will for free and open access to public data was seen in the hiQ vs LinkedIn case recently.
Scraping data proved daunting for hiQ Labs – a data analytics company that had been scraping publicly accessible data from LinkedIn. The latter chose to invoke the Computer Fraud And Abuse Act (CFAA) and accused hiQ of accessing the information “without authorization”. However, in a landmark move, the U. S. Ninth Circuit Court of Appeals ruled in favour of hiQ Labs, thus paving the way for the “open internet”.
hiQ vs. LinkedIn
The CFAA is a federal cyber-security law that was created to prevent hacking of government security systems “without authorization”. But its vagueness of the term “authorization” meant that companies could mould it to fit their own needs whenever necessary, as in the hiQ vs. LinkedIn case. What hiQ did was simple, it would use scraped data to create HR-related analytics products. For instance, Keeper identified flighty employees, while Skill Mapper would assess employees and find gaps in the workforce. But then LinkedIn launched a similar set of products in 2017, and that is when the scenario started going south.
On May 23, 2017, it sent a cease and desist letter to hiQ demanding that hiQ stop scraping data off of it. Two weeks later, hiQ filed suit for injunctive relief against LinkedIn.
It was clear to the court that hiQ would not survive as a company if not for the data from LinkedIn. Furthermore, the data on LinkedIn was publicly available, as users had not kept the information password encrypted. “There is little evidence that LinkedIn users who choose to make their profiles public actually maintain an expectation of privacy, ” the court said.
LinkedIn’s privacy policy stated that “any information you put on your profile and any content you post on LinkedIn may be seen by others. ” The odds were in favour of hiQ.
hiQ claimed for tortious interference of contract- LinkedIn was simply trying to market its products while throwing its competitor under the bus. While LinkedIn deemed the aggressive competition legal, the court did not.
LinkedIn tried to play the CFAA card. According to the law, “whoever… intentionally accesses a computer without authorization or exceeds authorized access, and thereby obtains… information from any protected computer… shall be punished, ” by fine or imprisonment. Further, “any person who suffers damage or loss by reason of a violation” of that provision may bring a civil suit “against the violator to obtain compensatory damages and injunctive relief or other equitable relief. ”
However, the data was not protected by a user ID and password and hence, LinkedIn’s argument became moot. The court ruled that CFAA did not apply to the case. The data was public; no unlawful “breaking and entering” took place.
The problem with CFAA
While it is a major win for data analytics, it also sheds light on a case of the Ninth Circuit that has managed to blur the outreach of the CFAA – the Facebook v. Power Ventures, a ruling that was also cited in the cease and desist letter of LinkedIn.
Power Ventures was a company that allowed an individual to manage all their social media accounts from one place. Unlike LinkedIn, where the data was publicly available, Power Ventures would ask for consent from the user. Therefore, it was the user that granted Power Ventures access to the data and not Facebook. Hence, though the company was “within authorization” in a way, it was still found to violate the CFAA.
There lies the trouble with the CFAA. While in theory, it should prevent hacking, it has become nothing more than a tool for major corporates. Every large enterprise interprets the law in its way and uses it to its advantage. Power Ventures was just an add-on feature that the user chose for himself; hiQ created analytical products that LinkedIn set its eyes on, and since the bigger companies wanted these third parties out of their forte, they called on the mighty CFAA.
While the court has located the lock on invoking the CFAA anytime one saw fit, it has still not shut the door completely. The more recent Stackla v. Facebook found yet another platform that got into controversy via web scraping.
With new cases popping up now and then, it will eventually fall on the court to clarify the CFAA and terms like “without authorization”. Data is present everywhere and creating a distinction between the legal and the illegal becomes of prime importance. The monopoly of data would be dangerous for innovation, and in the world of the fast-paced Internet, innovation is everything.
Conclusion
With the win in its bag, hiQ has cleared the path for the application of open web data. Web crawling and extracting is the cheapest way to gather data, and for far too long has been seen as a sceptical approach. One must understand that the only way small and big companies can compete in a level playing field is if the Internet and the data present on it remains free to use for all.
Can Google claim that the data it shows for a search result is its own? Can Wikipedia stop us from learning from its pages? After all, most of the information available in the public domain of the internet belongs to individuals or the market, and no company can claim to have a monopoly over it. What companies can compete on instead, is how well they can use the data and what services they can create. These services can digest the open data and produce a valuable output that can be used by businesses.
Scraping Job Data For Employers With The Indeed API

Scraping Job Data For Employers With The Indeed API

Table of Contents
1. What is the Indeed API?
2. How to Scrape indeed
3. Benefits of Using an Indeed Job Scraper
4. How to Export Data from Indeed
Indeed is a website that helps connect employers and job seekers through job postings, company reviews, salary data, and more. Because the Indeed site is full of relevant data, organizations can extract job data from the Indeed API for analysis. Web scraping, which is the automatic extraction of data from a webpage, is the best tool for extracting data from Indeed quickly, cheaply, and securely. Through scraping Indeed, an organization can establish a competitive salary, gain understanding of employee sentiment and values, find great candidates, and build a realistic budget for hiring employees and outside contractors. Once extracted, the Scraping Robot API helps you export the data directly into your preferred analysis program. With useful job data and web scraping tools, your organization can make smart, data-driven choices for the future.
What is the Indeed API?
The Indeed job search API helps users find job postings that fit their experience, salary expectations, location, and more. When you search for “marketing jobs, ” the Indeed API shares that data with the server which interprets it and presents you with relevant search results. The API is a messenger of sorts. Within Indeed, there is tons of useful job data including:
Job title
Job description
Salary
Location
Hours
Requirements
Company information
Candidate information
An API, or Application Programming Interface, is a software intermediary that allows applications to interact and securely share data. APIs make it possible to do things like send online messages, shop online, and check the weather on your phone.
How to Scrape Indeed
While you can manually extract data from Indeed, this process is time consuming, expensive, and requires a team. Web scraping is the automatic extraction of data from a web page. This process is cost-efficient and secure, and it provides your team with more time to focus on analysis and action. Using the API for Indeed job scraping makes it easier to manage large data sets such therefore making it an essential tool for larger organizations. But scraping is also ideal for small businesses unable to create their own data department.
Web scraping jobs from Indeed
In order to web scrape job postings on Indeed with an API, you first must search Indeed jobs by title. Without finding relevant job descriptions, you won’t extract useful data. Using a generic HTML scraper involves inputting the job posting URL and receiving the entire webpage data as output. But while the easiest method, you’ll still have to organize the data. Scraping Robot’s Indeed modules are built to recognize and organize Indeed data while scraping. Our Indeed modules include a salary scraper, a company review scraper, and a job scraper. Using an Indeed-specific scraper makes it easier to understand the data and generate insights. Whichever method you choose, learning how to scrape descriptions for jobs is indeed the first step to understanding your organization and its reputation among employees.
Benefits of Using an Indeed Job Scraper
Once you learn how to use an instant data scraper for indeed, you can start to reap some of the many organizational benefits that make it easier to attract talent and make competitive offers.
Establish competitive salary
In order to attract high-level talent, your organization has to offer a competitive salary and benefits. The easiest way to establish a competitive salary range is through scraping salary data on Indeed. Find jobs with similar requirements, time commitments, and responsibilities to understand how your competitors are compensating comparable employees. Since job seekers are likely applying to your competitors as well, it is important to offer a fair salary that is open to negotiation based on experience. While there are other aspects to consider when accepting a new job, salary is one of the most important. Lowballing employees is a turn off to talent and harmful to your organization’s reputation.
Understand Employee sentiment
In addition to competitive pay, employees value a supportive and inclusive company culture. When seeking work, people use online company reviews on Indeed and other job sites to get a glimpse of what life might be like if they work for a specific company. However, company reviews are about more than avoiding bad bosses and other professional red flags. Company reviews also reflect the values and structure of an organization. Even if your company culture is attractive to a candidate, they might want a small team instead of a large corporation. Scraping company reviews is essential for both employers and job seekers. For employers, company reviews reveal employee sentiment. While your organization might be doing internal satisfaction reviews, online reviews also influence your reputation amongst potential employees. Therefore scraping Indeed review is both an organizational diagnostic tool and a glimpse into employee sentiment. Companies can use common complaints or compliments to understand what they are doing right and where to improve. Scraping reviews makes company values clearer because when reviews are extracted as web data, the repeating phrases and words are easier to spot. Once these patterns reveal themselves, organizations will have a sense of their perception among employees (past and present) and therefore their reputation among job seekers.
Find candidates
On the other end of the process, organizations are flooded with online applications for every job post. Using a web scraper to get candidate information from Indeed ensures you’ll only spend time looking at qualified candidates based on listed job skills and requirements. Because the interview process takes time from both the employers and job seekers, getting straight to the best candidates is the best way to ensure everyone’s time is respected and that you don’t end up having to pick between many candidates.
Build a budget
While using Indeed to find full-time employees is great, there is also lots of salary information for different contractors. If you’re a small business owner, this salary information is helpful when creating a budget for outside contracting (production, packaging, social media, security, crew members, childcare, and basically any other service you can think of. If you are starting out, it is hard to know if you’re getting a fair deal. Scraping contractor salary information makes it easier to budget for every part of your process by creating expectations when you’re building an organization or small business.
How to Export Data from Indeed
Once you’ve scraped job data with the Indeed API, you’ll have to manage and export data to your preferred analysis program. Scraping Robot’s API makes this possible.
Scraping Robot API
Scraping Robot’s API is built to help you directly export extracted data from web scraping into an analysis program of your choice. Managing lots of data sets and exporting them individually is time consuming and difficult. Our API makes it efficient to directly export data from scraping. This process makes it easier to manage larger data sets and access the knowledge of our team. The API allows you to combine different sets of data for a more accurate analysis. If this sounds like the solution for your organization, check out our API page.
Conclusion
The job search is exhausting as employers and employees constantly look for a good fit. Indeed, one of the most popular job sites, makes this connection easier to find. Because of all the useful job, company, and salary data available, extracting data from the Indeed API yields valuable insights for organizations of all sizes. Using an Indeed web scraper makes it easy to determine a competitive salary, understand employee values, find candidates, and create a budget for employment and outside contractors. Once extracted, the Scraping Robot API makes it easy to directly export Indeed data into an analysis program of choice. Web scraping Indeed and conducting professional analysis will help your organization find and secure talented individuals for your team.
The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.

Frequently Asked Questions about job board scraping

What is Job scraping?

Some job sites use a process called “scraping” to gather information about open positions found around the web (for example, on your careers page). They constantly look for new job posts around the web and “scrape” those posts to put them on their own website without the consent of your organization.Jul 28, 2021

Is Job scraping legal?

In late 2019, the US Court of Appeals denied LinkedIn’s request to prevent HiQ, an analytics company, from scraping its data. The decision was a historic moment in the data privacy and data regulation era. It showed that any data that is publicly available and not copyrighted is fair game for web crawlers.

Is it legal to scrape data from indeed?

LinkedIn ⁠— It Is Indeed Legal to Scrape Publicly Available Web Data. Stairway to heaven, If you’re in the business of web scraping, that is. They claim data from the users as their own. …Oct 14, 2019

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