The Meeting of Minds: Forging Social and Intellectual Networks within Universities
How are social and intellectual relations structured and given shape within research universities? To answer these questions, we test to what extent various theoretically predicted processes explain the dynamics of academics’ networks of collaboration and shared language use in a unique longitudinal...
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Society for Sociological Science
2020-09-01
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doaj-113b0a88db4742059007f67429599ab62020-11-25T03:42:33ZengSociety for Sociological ScienceSociological Science2330-66962330-66962020-09-0171843346410.15195/v7.a18The Meeting of Minds: Forging Social and Intellectual Networks within UniversitiesTobias H. Stark0J. Ashwin Rambaran1Daniel A. McFarland2Utrecht UniversityUniversity of MichiganStanford UniversityHow are social and intellectual relations structured and given shape within research universities? To answer these questions, we test to what extent various theoretically predicted processes explain the dynamics of academics’ networks of collaboration and shared language use in a unique longitudinal data set (1994 to 2005) of 2,631 faculty at a large private American university. Using the latest advances in stochastic actor-oriented models (in RSiena) and text analysis, we found that social and intellectual relations are clustered and centralized on bridging faculty who form a broader interdisciplinary hub of research in the university, and that, over time, this hub disseminated its style of (interdisciplinary) research to other faculty. These networks are shaped by selection based on age, gender, race, and academic rank as well as the coevolution of social and intellectual relations over time. Clear differences emerge in science, technology, engineering, and mathematics (STEM) fields and are strongly driven by structural mechanisms of clustering and centralization, whereas non-STEM fields (social sciences and humanities) are strongly driven by personal preferences of faculty members.https://sociologicalscience.com/articles-v7-18-433/knowledge organizationsacademic collaborationsociology of sciencemultiplex network analysislongitudinal social network analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tobias H. Stark J. Ashwin Rambaran Daniel A. McFarland |
spellingShingle |
Tobias H. Stark J. Ashwin Rambaran Daniel A. McFarland The Meeting of Minds: Forging Social and Intellectual Networks within Universities Sociological Science knowledge organizations academic collaboration sociology of science multiplex network analysis longitudinal social network analysis |
author_facet |
Tobias H. Stark J. Ashwin Rambaran Daniel A. McFarland |
author_sort |
Tobias H. Stark |
title |
The Meeting of Minds: Forging Social and Intellectual Networks within Universities |
title_short |
The Meeting of Minds: Forging Social and Intellectual Networks within Universities |
title_full |
The Meeting of Minds: Forging Social and Intellectual Networks within Universities |
title_fullStr |
The Meeting of Minds: Forging Social and Intellectual Networks within Universities |
title_full_unstemmed |
The Meeting of Minds: Forging Social and Intellectual Networks within Universities |
title_sort |
meeting of minds: forging social and intellectual networks within universities |
publisher |
Society for Sociological Science |
series |
Sociological Science |
issn |
2330-6696 2330-6696 |
publishDate |
2020-09-01 |
description |
How are social and intellectual relations structured and given shape within research universities? To answer these questions, we test to what extent various theoretically predicted processes explain the dynamics of academics’ networks of collaboration and shared language use in a unique longitudinal data set (1994 to 2005) of 2,631 faculty at a large private American university. Using the latest advances in stochastic actor-oriented models (in RSiena) and text analysis, we found that social and intellectual relations are clustered and centralized on bridging faculty who form a broader interdisciplinary hub of research in the university, and that, over time, this hub disseminated its style of (interdisciplinary) research to other faculty. These networks are shaped by selection based on age, gender, race, and academic rank as well as the coevolution of social and intellectual relations over time. Clear differences emerge in science, technology, engineering, and mathematics (STEM) fields and are strongly driven by structural mechanisms of clustering and centralization, whereas non-STEM fields (social sciences and humanities) are strongly driven by personal preferences of faculty members. |
topic |
knowledge organizations academic collaboration sociology of science multiplex network analysis longitudinal social network analysis |
url |
https://sociologicalscience.com/articles-v7-18-433/ |
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