This article presents the design and implementation of a network intervention to foster scientific collaboration at a research university, and describes an experimental framework for rigorous evaluation of the intervention's impact. Based on social network analysis of publication and grant data, an innovative type of research funding program was developed as a form of alteration of the university's collaboration network. The intervention consisted in identifying research communities in the network and creating a new collaborative relation between pairs of unconnected researchers in selected communities. The new collaboration was created to maximally increase the overall cohesion of the target research community. In order to evaluate the impact of the program, we designed a randomized experiment with treatment and control communities based on the Rubin Causal Model approach. The paper describes the intervention design, reports findings from the program implementation, and discusses the statistical framework for future evaluation of the intervention.

Connecting the dots: implementing and evaluating a network intervention to foster scientific collaboration and productivity / V. Leone Sciabolazza, R. Vacca, C. McCarty. - In: SOCIAL NETWORKS. - ISSN 0378-8733. - 61(2020), pp. 181-195. [10.1016/j.socnet.2019.11.003]

Connecting the dots: implementing and evaluating a network intervention to foster scientific collaboration and productivity

R. Vacca;
2020

Abstract

This article presents the design and implementation of a network intervention to foster scientific collaboration at a research university, and describes an experimental framework for rigorous evaluation of the intervention's impact. Based on social network analysis of publication and grant data, an innovative type of research funding program was developed as a form of alteration of the university's collaboration network. The intervention consisted in identifying research communities in the network and creating a new collaborative relation between pairs of unconnected researchers in selected communities. The new collaboration was created to maximally increase the overall cohesion of the target research community. In order to evaluate the impact of the program, we designed a randomized experiment with treatment and control communities based on the Rubin Causal Model approach. The paper describes the intervention design, reports findings from the program implementation, and discusses the statistical framework for future evaluation of the intervention.
Community detection; Network intervention; Rubin causal model; Scientific collaboration; Team science
Settore SPS/07 - Sociologia Generale
2020
Article (author)
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S037887331830354X-main.pdf

accesso riservato

Tipologia: Publisher's version/PDF
Dimensione 1.34 MB
Formato Adobe PDF
1.34 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/902043
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 15
  • ???jsp.display-item.citation.isi??? 13
social impact