University of Michigan: Study Finds Economist Retweets Benefit Doctoral Job Seekers in Visibility and Outcomes
Job candidates often seek any advantage to secure employment, and a new study investigates a less-than-typical source: retweets from researchers on social media.
The University of Michigan study indicates that when prominent economists retweet job market papers—which are doctoral students’ main academic work for job applications—with comments, it significantly boosts visibility and recognition for candidates.
Researchers looked at the causal effects of social media promotion on Twitter (now X) on job market outcomes and evaluated the potential of social media promotion to improve job prospects for job market candidates, especially underrepresented groups.
The intervention involved 519 candidates in the 2022-2023 economics job market. The researchers first tweeted about each candidate’s job market paper from a dedicated Twitter account called ‘Econ Job Market Helper,’ which had more than 2,000 followers. Then, for a randomly selected subset of candidates, they asked established economists with more than 4,000 followers to ‘quote-tweet’ (retweet with comments) these posts.
The results showed a 442% increase in views and a 303% increase in likes for job market papers in the study’s treatment group. In addition, women in the treatment group received one more job offer than their counterparts in the control group.
“Social media has emerged as a popular tool for researchers to rapidly and broadly disseminate their latest findings. Promoting one’s work increases its chances of being noticed,” said study lead author Jingyi Qiu, doctoral student at U-M’s School of Information. “Social media platforms give us new tools to reach out to people beyond our departments.”
Beyond increasing the attention on a job candidate’s research, there are more benefits for a young economist being active on social media.
“Many senior economists are very happy to share tips on how to navigate academia and write good papers,” Qiu said.
The study, which appeared recently on SSRN, a social science working paper archive, was co-written by Yan Chen and Alain Cohn of the U-M School of Information and Alvin Roth of Stanford University.