Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 75-79). / When searching for jobs, job applicants are not only motivated by monetary compensation alone, the meaning and social effects of the work also matter. Pro-social motivation, the desire to have a positive impact on other people or social collectives also play an important role in job searching. On the other hand, organizations also have many incentives to promote pro-social jobs during the recruiting processes and accordingly design pro-social characteristics in job postings. Using latest machine learning techniques, we could possibly quantify pro-social characteristics in massive amount of job postings and potentially predict pro-social messages advertised in online job postings. In this thesis, we take up the challenge of developing novel measures of pro-social that satisfactorily address the problems identified with existing measures of pro-social. We proposed implementations of two different machine learning approaches to quantitatively measure pro-social messages from over five million online job postings documentation and effectively predict pro-social jobs, with 79% and 94% prediction accuracy yield from methodology I and methodology II respectively. Based on those approaches, we evaluate the model performance and measure correlation of industries' use of pro-social messages in job postings to compare the effectiveness of two models on several metrics. / by Zhuoqiao Hong. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/132825 |
| Date | January 2020 |
| Creators | Hong, Zhuoqiao. |
| Contributors | Massachusetts Institute of Technology. Engineering and Management Program., System Design and Management Program., Massachusetts Institute of Technology. Engineering and Management Program, System Design and Management Program |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 82 pages, application/pdf |
| Rights | MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided., http://dspace.mit.edu/handle/1721.1/7582 |
Page generated in 0.0081 seconds