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Field
Abstract
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Before
Does social media exposure affect job market outcomes? We will collect job market candidates’ demographic information and a summary of their job market paper. We will then tweet every participant’s JMP. We plan to conduct a field experiment to evaluate whether and the extent to which social media exposure might impact job market outcomes. Outcome data will be collected at the end of the job market.
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After
We conducted a field experiment to investigate the causal impact of social media promotion on job market outcomes for Economics job market candidates (JMCs), with a particular focus on under-represented groups such as women, racial and ethnic minorities, and the LGBTQ+ community. We asked economist "influencers" with more than 4,500 followers on Twitter to quote-tweet a random subset of job market paper tweets on Econ Job Helper. We will subsequently measure the impact of this intervention on job market outcomes. Preliminary analysis reveals an increase in the visibility of job market papers for the treatment group, as their tweets receive higher numbers of likes, retweets, and URL clicks. Currently, job market outcomes are being collected to further analyze whether social media promotion can help JMCs receive more job interviews, fly-outs, and job offers. The results of this study will enhance our understanding of the efficacy of social media promotion in influencing job market outcomes for junior scholars, especially for those from under-represented groups in the academic job market.
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Field
Last Published
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Before
November 04, 2022 01:39 PM
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After
May 08, 2023 06:50 PM
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Field
Primary Outcomes (End Points)
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Before
job market outcomes
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After
Number of interviews / fly-outs / job offers received on different types of jobs
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Field
Primary Outcomes (Explanation)
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Before
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After
We will collect data on job interviews, fly-outs and job offers via a post-market survey.
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Field
Randomization Method
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Before
Done by a computer.
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After
Please refer to our pre-analysis plan
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Field
Planned Number of Clusters
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Before
800 subjects
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After
525
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Field
Planned Number of Observations
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Before
800 subjects
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After
525
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Field
Sample size (or number of clusters) by treatment arms
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Before
400 in the treatment group and 400 in the control group
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After
Treatment: n = 247 (URG: 150; non-URG: 97)
Control: n = 278 (URG: 81, non-URG: 197)
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Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
0.2
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After
0.25 (main effect)
0.34 (subgroup effect)
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Field
Secondary Outcomes (End Points)
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Before
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After
Satisfaction with job placement
Twitter influence index: impressions, retweets, URL clicks, detail expands, engagements, likes, replies etc.
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Field
Secondary Outcomes (Explanation)
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Before
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After
We will collect satisfaction with job placement via our post-market survey.
We will collect Twitter influence index via Twitter Analytics.
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