Project info
Project name
10.3 The Link between Cooperation and Social Networks: Exclusion or Stimulation of Defectors?
Work package
- Theory
Sustainability threat
- External Shocks
Challenge
- Network co-evolution
Study info
Related studies according to this researcher
A bad barrel spoils a good apple: How uncertainty and networks affect whether matching rules can foster cooperation
The role of personality traits in the formation of friendship and preference-for-collaboration networks among first-year students in higher education
Description of Study
Theoretical and experimental work has shown that cooperation selection (CS; “selecting similar others”) and social influence (SI; “do as others do”) can solve the problem of cooperation in networks. However, it remains unclear whether CS and SI promote cooperation in settings where i) actors try to optimize decisions based on myopic stochasticity rather than strategic anticipation and ii) both mechanisms operate alongside further processes occurring in real-life network formation, such as reciprocity and transitivity. Whether cooperation “spreads,” “segregates,” or “dies out” depends on the exact mix of CS and SI with these other social processes. To explore this in an empirically realistic setting, we use data from 95 students as input for “what if” simulations in which we vary the strength of CS and SI relative to empirically observed levels. Our simulations reveal that cooperation benefits most when CS and SI are strongly positive. Through the combination of CS and SI, cooperators form dense local clusters, influencing their peers to keep cooperating while insulating themselves from social influence from defectors. Our model also highlights a downside for defectors: Some remain socially excluded and are not stimulated to cooperate, diminishing their chances to change from defection to cooperation.
Study research question
It remains a question of whether, and if so, how and to which extent cooperation selection (CS) and social influence (SI) promote cooperation when accounting for the “messiness” of real life. To study this, we utilize longitudinal empirical friendship and cooperation data from 95 students in higher education. To do so, we rely on empirically calibrated agent-based models.
Collection provenance
- External data
- -
Collection methods
- Questionaire
- Longitudinal survey
- Simulation
Personal data
Yes
External Source
Source description
File formats
Data types
- Structured
Languages
Coverage start
Coverage end
01/09/2013
01/09/2014
Spatial coverage
Groningen, University of Groningen, Netherlands
Collection period start
—
Collection period end
—
Variables
Unit
Unit description
Sample size
Sampling method
Individuals
university students (freshmen)
95
questionnaire
Other
agents
95
simulation
Hypothesis
Theory
Counterfactual 1 assesses whether strong SI promotes cooperation in networks in which the majority is cooperative while other processes affecting network formation and cooperation match those observed in our empirical setting.
selection and influence
Counterfactual 2 addresses whether strong CS gives rise to segregated cooperation over time while other processes affecting network formation and cooperation match those observed in our empirical setting.
selection and influence
Counterfactual 3 assesses whether the combination of CS and SI spreads or founders cooperation over time, or gives rise to segregated configurations when other processes affecting network formation and cooperation match those observed in our empirical setting.
selection and influence
Variable type
Variable name
Variable description
Dependent variable
cooperation
whether one defects (0), cooperates (2), or remains neutral in behavior (1)
Dependent variable
network relation
Whether one is nominated as network partner or not
Discipline-specific operationalizations
Conflict of interest
Data packages
Publications
Documents
Filename
Description
Date
Ethics
Ethical assessment
No
Ethical committee