Finding Doppelgängers in Scopus: How to Build Scientists Control Groups Using Sosia

23 Pages Posted: 8 Dec 2020

See all articles by Michael E. Rose

Michael E. Rose

Max Planck Institute for Innovation and Competition

Stefano Baruffaldi

University of Bath; Max Planck Institute for Innovation and Competition

Date Written: December 3, 2020

Abstract

The construction of control groups of scientists is often a daunting effort. This paper presents sosia, an open-source Python-based software designed to query efficiently the Scopus database via RESTful API. sosia searches for researchers with publication profiles similar to a given researcher up to a given year based on all main standard bibliometric indicators. The user can choose flexibly a set of parameters to restrict the search to more or less narrow boundaries upfront and obtain additional similarity indicators to select a subset of authors after the search. Advanced settings also allow to narrow the search to a list of affiliations and to minimize the possible errors arising from ambiguous author profiles. One basic search can be set up in a few command lines and the average time of computation goes between 60 and 300 minutes. We discuss the functioning, characteristics, limitations and possible extension of the software.

Keywords: Statistical Software, Control Group, Diff-in-Diff, Scopus

JEL Classification: C00, A14

Suggested Citation

Rose, Michael and Baruffaldi, Stefano, Finding Doppelgängers in Scopus: How to Build Scientists Control Groups Using Sosia (December 3, 2020). Max Planck Institute for Innovation & Competition Research Paper No. 20-20, Available at SSRN: https://ssrn.com/abstract=3742602 or http://dx.doi.org/10.2139/ssrn.3742602

Michael Rose (Contact Author)

Max Planck Institute for Innovation and Competition ( email )

Marstallplatz 1
Munich, Bayern 80539
Germany

HOME PAGE: http://https://www.ip.mpg.de/en/persons/rose-michael.html

Stefano Baruffaldi

University of Bath ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

Max Planck Institute for Innovation and Competition ( email )

Marstallplatz 1
Munich, Bayern 80539
Germany

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