No need to take a career quiz - a new study suggests social media can help find the best job match for your personality

The researchers took 10 occupations and over 9,500 user samples to run machine learning algorithms that determined if jobs can accurately be predicted from users' traits or values categorized by Watson. The researchers used five classification predictive modeling algorithms. These algorithms attempt to automatically predict what job a person holds from their traits and values.

When Big Five traits and basic values were used together to predict a user's occupation, the algorithms were more accurate, predicting users' jobs over 70% of the time, than when values and traits were used alone. This accuracy means it could be possible to predict the best occupation for someone based on their digital fingerprint, and the personality traits implied by that fingerprint.

That means a future where people lean on their own social media posts to assist them in their job search could be possible.

"This creates the possibility for a modern approach to matching one's personality and occupation with an excellent accuracy rate," Kern said in a news statement after the paper was published.

The study found that different digital fingerprints can be grouped together by what kinds of jobs social media users held. In total, they classified jobs into 20 clusters using Big Five traits and basic value scores.

Clustering is used in data science to group similar data points together based on an attribute or attributes of the data; the researchers used the job's average for each of 10 values and traits to create clusters.

According to the paper, there was "greater alignment for similar occupations." For instance, managers were clustered in one group of users with similar traits and values, education jobs in another, and developers and programmers in a different one.

Interestingly, the majority of results the researchers found aligned with how they would be categorized in the US Standard Occupation Classification (SOC) system. That means the researchers were able to use Twitter users' digital fingerprints to create groups that were similar to the categories used by the US Bureau of Labor Statistics to classify jobs, suggesting that the clusters found in the study correspond to real-world job categories.

Although the majority of occupations were part of a cluster that was similar to their SOC category, there were some points that fell into a different cluster on the vocation map. The researchers suggested in the paper that this could be because of the skills required in the occupation; those skills might be similar to the requirements of an occupational category found in a different cluster.

Before the main data clustering study, the researchers first wanted to see if it was even possible to use social media to find differences in personality among people in different jobs. In order to do so, they took a smaller subset of their collected data.

Based on that smaller sample — over 1,000 users and nine occupations — top GitHub contributors, who are usually programmers and software developers, tended to have low scores on agreeableness and conscientiousness but high scores on openness. Meanwhile, professional tennis players tended to be the opposite, with low scores on openness, yet high scores on agreeableness and conscientiousness.

These results suggest that tennis players' personalities can be classified as typically more cooperative and kind, whereas software engineers are more open to new experiences and ideas.

In addition to software engineers, the researchers found that scientists in different fields typically were more open and less agreeable or conscientious.

Maybe you're unhappy with your job, but don't want to change because you're unsure what you can do outside your field.

Research like this study could suggest good alternative career paths for someone who wants to find a new job where they can find success with their skills and personality traits. If social media data can help predict a match between personality and occupation, analyses like these could provide another tool for job-seekers.

"By better understanding the personality dimensions of different jobs we can find more perfect matches," said McCarthy in a news statement.

The researchers said in the published paper that they believe their findings can help people find jobs that match their personality as new occupations emerge and others become obsolete.