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Reaching for Unique Resources: Structural Holes and Specialization in Scientific Collaboration Networks

Journal of Social Structure
Volume 21 (2020): Issue 1 (January 2020)
By:
Open Access
|Jul 2020

Figures & Tables

Figure 1:

Collaboration as a process of pooling resources.
Collaboration as a process of pooling resources.

Figure 2:

Burt’s redundancy in egocentric networks.
Burt’s redundancy in egocentric networks.

Figure 3:

Implications of structural holes and specialization hypotheses. (A) The more redundant the alters are, the more similar resources they contribute. Ego acquires similar resources from Actors 1, 2, and 3 because they are redundant (B) specialization only takes place in a tightly collaborating group (0-1-2-3). Ego acquires different resources from actors 1, 2, and 3 because they specialize within the group of 0, 1, 2, and 3.
Implications of structural holes and specialization hypotheses. (A) The more redundant the alters are, the more similar resources they contribute. Ego acquires similar resources from Actors 1, 2, and 3 because they are redundant (B) specialization only takes place in a tightly collaborating group (0-1-2-3). Ego acquires different resources from actors 1, 2, and 3 because they specialize within the group of 0, 1, 2, and 3.

Figure 4:

Collecting data on collaboration networks.
Collecting data on collaboration networks.

Figure 5:

Collaboration network.
Collaboration network.

Figure 6:

Network of resource flows.
Network of resource flows.

Figure 7:

Estimates of fixed effects (dots) and Bootstrap confidence intervals (bars) from random intercept models for similarity of resources acquired by ego. Reference category for ego’s degree: PhD. Confidence intervals are based on 1,000 draws. Detailed results can be found in Appendix A1 in Tables A.1 and A.2.
Estimates of fixed effects (dots) and Bootstrap confidence intervals (bars) from random intercept models for similarity of resources acquired by ego. Reference category for ego’s degree: PhD. Confidence intervals are based on 1,000 draws. Detailed results can be found in Appendix A1 in Tables A.1 and A.2.

Figure 8:

Effect plot of pairwise redundancy on resource similarity based on Model 3 assuming average ego-network size, alters from different departments, of different degree, and ego with a PhD degree.
Effect plot of pairwise redundancy on resource similarity based on Model 3 assuming average ego-network size, alters from different departments, of different degree, and ego with a PhD degree.

Basic information about the respondents in the sample

IDCityGenderScientific degreeBranch of scienceNetwork size (degree)
201AMalePhDTechnical sciences10
202AMalePhDSocial sciences7
203AMaleProfessorTechnical sciences9
204AMalePhDTechnical sciences8
205AFemalePhDLife sciences4
206AMalePhDNatural sciences4
207AFemalePhDSocial sciences10
208AFemalePhDHumanities5
209BFemaleHabilitated PhDLife sciences9
210BMalePhDHumanities8
211BMaleHabilitated PhDLife sciences10
212BFemalePhDSocial sciences10
213BMaleProfessorNatural sciences7
214BFemalePhD studentNatural sciences/Engineering4
215BFemaleHabilitated PhDLife sciences10
216BMaleHabilitated PhDNatural sciences10
217BMaleProfessorTechnical sciences10
218CFemaleHabilitated PhDHumanities10
219CMalePhDEngineering10
220CMaleHabilitated PhDNatural sciences6
221DMalePhDEngineering9
222DFemaleHabilitated PhDLife sciences10
223DFemaleHabilitated PhDHumanities7
224DMalePhDHumanities10
225DMalePhDNatural sciences10
226DFemaleHabilitated PhDNatural sciences10
227DMaleProfessorHumanities9
228DMaleHabilitated PhDLife sciences7
229DFemalePhD studentSocial sciences6
230DFemalePhD studentTechnical sciences7
231EFemaleHabilitated PhDSocial sciences7
232EFemalePhDSocial sciences11
233EFemalePhD studentTechnical sciences6
234EFemalePhDSocial sciences10
235EMalePhDNatural sciences/Engineering6
236EFemaleHabilitated PhDNatural science9
237EFemalePhDNatural science7
238FMaleProfessorTechnical sciences15
239FMaleProfessorTechnical sciences9
240DMalePhD studentHumanities7

Pairwise redundancy scores for the example collaboration network_

23456789
110220000
2 00.50.50000
3 000000
4 20000
5 0000
6 100
7 00
8 0

Random intercept models for alter contributions_ Null model: σ U 2 = 0_01 , σ R 2 = 0_053 , AIC=–56_91_

VariableModel 1Model 2Model 3
EstimateSEEstimateSEEstimateSE
Random effects
Ego0.08–0.08–0.08–
Residual0.05–0.05–0.05–
Fixed effects
Intercept0.170.080.150.080.070.08
Egos degree: PhD hab.0.060.040.060.040.060.04
Egos degree: MA0.030.060.030.060.020.06
Egos degree: professor0.070.040.070.040.070.04
Network size-0.010.01-0.010.01-0.010.01
Alters same degree0.110.010.100.010.110.01
Alters same department0.070.020.050.020.050.02
Pairwise redundancy––0.010.00––
Pairwise redundancy (0<P<1)––––0.120.02
Pairwise redundancy (P>1)––––-0.010.01
Model statistics
AIC-121.51–-127.58–-150.47–
df9.00–10.00–11.00–

Directions of effects of redundancy on similarity of acquired resources under H1 and H2_

HypothesisEffect of redundancy on similarity of resources acquired by ego
H1: Structural holes+
H2: In-group specialization−

Model comparison statistics for alter contributions_

ModelDfAICDeviance x 2 x 2 df p-value
Null model3-56.91438-62.91438–––
Model 19-121.50963-139.5096376.59525960.000
Model 210-127.57490-147.574908.06526210.005
Model 311-150.46507-172.4650724.89017210.000

Descriptive statistics of variables used in the analysis_

VariableMin.MeanSDMax.
Level: Alter-alter
Alters same degree00.3060.4611
Alters same department00.2330.4231
Pairwise redundancy01.8292.4088
Similarity of alter contributions00.1610.2461
Level: Ego
Egos degree: MA00.1000.3041
Egos degree: PhD00.4000.4961
Egos degree: PhD hab.00.2250.4231
Egos degree: professor00.2750.4521
Network size59.3502.29316
DOI: https://doi.org/10.21307/joss-2020-001 | Journal eISSN: 1529-1227 | Journal ISSN: 2300-0422
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Language: English
Page range: 1 - 34
Published on: Jul 30, 2020
Published by: International Network for Social Network Analysis (INSNA)
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Collaboration networks,
Structural holes,
Specialization,
Sociology of science
Related subjects:
Social sciences,
Social sciences, other

© 2020 Michał Bojanowski, Dominika Czerniawska, published by International Network for Social Network Analysis (INSNA)
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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