“We’ve moved from a very rigid resume, with little information regarding education and work history, to having details for every update,” said Gustavo Denicolay, MBA—founder of the consulting firm Adaptive and professor in the Data Science master’s programs at the University of Buenos Aires, the Buenos Aires Institute of Technology, and Austral University—during the conference “Data Science Applied to LinkedIn.”
The online event, organized by the Graduate School of Business at Universidad ORT Uruguay, was part of the Management and Business Lecture Series. It took place on Wednesday, November 25, 2020.
The Potential of LinkedIn
LinkedIn provides companies with valuable information. As Denicolay explained, this platform allows users to list all the courses and credentials they have: “This is very useful for recruiters. They can see who the most motivated employees are—the ones trying to stand out.”
Companies can even reach out to candidates with promising profiles to let them know that, if they complete certain courses or acquire specific skills, they might be hired.
“Resumes have changed in such a way that, whereas before people tried to hide frequent job changes—since high turnover could be viewed negatively by employers—now, on the contrary, they aim to highlight every achievement they’ve earned,” said Denicolay.
In the context of this ongoing curriculum update, the expert cautioned against listing courses that are too short, as this can be counterproductive. “You have to know how to choose what to highlight, since what you select to include on LinkedIn is also an indicator of your overall view of work.”
By uploading virtually every course they take, without exception, people are providing LinkedIn with a goldmine of information. “We’ve gone from a very rigid resume, with limited details about education and work history, to having detailed information with every update to a resume,” Denicolay noted. “This provides a wealth of information to those looking to hire, as well as to those looking to change jobs or analyze this data.”
Data collection
The expert encouraged us to consider how all this information can be leveraged through data science. One way is through web scraping, a technique used to extract data from websites. “It’s not easy to scrape LinkedIn. This platform has a private database. It doesn’t want others to obtain data from its platform. So it puts up technical barriers to prevent mass downloading of resumes. It detects very quickly if a bot is downloading data and blocks it.”
As for how to proceed once the information has been processed using data analytics, the expert explained that predictive models can be created. “More and more, people are sharing information on LinkedIn because it serves as their online showcase,” he noted. “The data is public—very difficult to download, but public.”
Finally, Denicolay asked himself, “Where else do people voluntarily post the courses they’re taking and the jobs they’re working on? On what other websites do people share everything, and is that information publicly available?”