The Rise of Machine Learning in the Academic Social Sciences

Charles Rahal, Mark D. Verhagen and David Kirk
Additional contact information
David Kirk: University of Oxford

No gydve, SocArXiv from Center for Open Science

Abstract: This short perspectives-style article explains recent trends and outlines three reasons to be even more optimistic about the future of Machine Learning in the academic Social Sciences.

Date: 2021-10-01
New Economics Papers: this item is included in nep-big and nep-cmp
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/6157477f17d227013885fbcf/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:gydve

DOI: 10.31219/osf.io/gydve

Access Statistics for this paper

More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().