Your Social Media Profile Can Now Predict The Right Career For You [STUDY]

People nowadays are spending significant time on Social media platforms, sharing and engaging with various types of content. Their expressive behaviour can now be used to suggest to them what could be the right career path they must walk on.

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Choosing the right career for yourself is almost equivalent to finding a needle in the haystack with so many career opportunities and alternatives available in today’s day and age. The average person today is said to hold close to 12 jobs in their entire lifetime. Also, 1 out of 3 employees is said to be underqualified for their current role, wherein 1 out of 4 is reportedly overqualified. It is also believed that the vast majority of people feel withdrawn at work globally and therefore, ending up in the wrong profession can turn out to be quite a common experience.

Up until now, self-report surveys have been one of the most popular methods to help one figure out their preferences related to career choices. These surveys are not only cumbersome but also could be easily faked and therefore, the authenticity of these survey tests have long been highly debated. Now, a new scientific paper has reportedly come up with an alternative to other imperfect and overly simplified career tests. And it involves your social media feed! In this case, your twitter feed to be exact!

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Researchers of this study used machine learning coupled with data from the Twitter feed in order to match one’s personality to its appropriate occupation. One of the study’s co-authors, Marian-Andrei Rizoiu said that the study is quite fascinating as it reportedly takes the big data approach to personality and career.

Tweets from over a whopping 130,000 Twitter users were analyzed by researchers Rizoiu and her colleagues to capture what they called personality profiles. According to the researchers, these personality profiles are essentially the collective traits and values that help shape who we are. These profiles were then further used for comparison with the careers that the users mentioned in their Twitter bios. After doing so, the researchers found out that the link between them was really strong. In fact, the link was so strong that they could finally use these personality profiles to correctly predict occupations with more than an excellent 70 per cent accuracy. Therefore, Rizoiu concluded that if a random personality profile was to be handed over to them without any other significant information, they would easily be able to guess their profession in 3 out of 4 cases.

Personality has long been connected to everything related to careers and hiring ability by past studies. It was found out that an employee was likely to earn 10 per cent more if his/her personality was well suited for their profession by a study conducted in 2017 as well.

The lead author of the study and an associate professor at the University of Melbourne’s Center for Positive Psychology, Peggy Kern believes that the study can open up huge possibilities to help people explore more interesting ways to go beyond the typical normal ways to make their career decisions.

However, Kiki Leutner, a business psychologist and data scientist at University College London, who was not involved in the study had a different point of view which should be taken note of. She mentioned that although the research makes a perfect use case of the social media data where one has access have a huge data set of people’s personalities in different locations, one can only happen look at the current state of things. The study aptly points out where exactly digitally extroverted people are more likely to work. However, it still remains unclear whether those extroverted people are really better in their chosen roles.

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Leutner further went on to express her concerns by saying that she fears that the findings of the study could easily start being misused by various businesses to use it as a new method to screen their employees.

Machine Learning: The Future of Career-Related Predictions?

Sure, career choices could soon be driven less by simply happenstance and more by data. Machine learning can only prove to be accurate and beneficial if the data or information it relies on is equally good and authentic. Therefore, for example, if the data being analyzed by the team has a particular minority group which is underrepresented, it would spew up an analysis with some pretty serious inaccurate and biased outcomes.

According to Kern, if machine learning is to be widely accepted and applied to screen employees, it has to have a solid chunk of reliable data as its foundation. It would also need to be proved that the traits that are being looked for in the digital personality profiles truly contribute to the performance in a certain occupation or profession. Therefore, until these important and crucial bases can be covered, this research and technology should strictly remain as an exploratory and experimental tool as it is more informational than prescriptive.

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