Week 9

Network position and performance

Published

December 10, 2025

Overview

This week addresses one of the central questions in network analytics: When do networks create value? We explore how structural position translates into tangible outcomes for individuals and organizations, drawing on two foundational theories of social capital:

  1. Bonding Social Capital (Coleman): Dense, closed networks create value through trust and cooperation. When your contacts know each other, reputation effects operate, social norms can be enforced, and cheating becomes costly. This is the theory of network closure.

  2. Bridging Social Capital (Burt): Sparse networks with structural holes create value through access to diverse information and brokerage opportunities. Individuals who span disconnected groups gain early access to non-redundant information and strategic control over information flows.

These perspectives represent a fundamental tension in network strategy: closure provides safety and trust, while brokerage provides opportunity and innovation. The optimal structure depends on what you are trying to achieve.

Prepare

Note📚

📖 Review:

📖 Required Readings:

Burt, R. S. (2004). “Structural Holes and Good Ideas.” American Journal of Sociology, 110(2), 349-399.

Focus on:

  • Structural holes: The “empty space” between disconnected groups that creates brokerage opportunities
  • Information benefits: How brokers access diverse, non-redundant knowledge before others
  • Good ideas: Evidence that network position predicts idea quality and career success

Coleman, J. S. (1988). “Social Capital in the Creation of Human Capital.” American Journal of Sociology, 94, S95-S120.

Focus on:

  • Closure and trust: How dense networks enable cooperation and reduce transaction costs
  • Reputation effects: Why cheating becomes costly when mutual friends can observe and sanction
  • Norm enforcement: How closed networks establish and maintain shared expectations

Participate

Note👥

📉 Slideshow: When Do Networks Create Value?

This presentation covers:

  • The theoretical framework: social capital vs. social homogeneity
  • Bonding social capital: network closure and the Coleman perspective
  • Bridging social capital: structural holes and the Burt framework
  • Measuring closure (clustering coefficient) and brokerage (betweenness, constraint)
  • Business applications: fraud detection, organizational networks, and board interlocks
  • The strategic tension between safety (closure) and opportunity (brokerage)

Practice

Note💻

Hands-on Analysis: Measuring social capital and brokerage

Apply the concepts from this week to analyze network position and its relationship to performance:

Exercise 1: Clustering and Closure

Using the network datasets from previous weeks, calculate and interpret:

  • Local clustering coefficients for each node
  • Network-level average clustering
  • Compare clustering across different types of networks (social vs. information vs. collaboration)

Exercise 2: Brokerage Position

Identify brokers and structural holes:

  • Calculate betweenness centrality to find nodes on shortest paths
  • Compute Burt’s constraint index to measure structural hole access
  • Visualize brokerage positions by coloring nodes by constraint level

Exercise 3: Position-Performance Relationship

If your network has performance data (e.g., sales, ratings, influence):

  • Correlate network position metrics with performance outcomes
  • Test whether brokers outperform actors in closed networks (or vice versa)
  • Consider what contextual factors might moderate these relationships

Perform

Note📝

Application Exercise: Network Audit

Choose an organization or professional context you are familiar with (your workplace, a student organization, an industry you follow):

  1. Map the informal network: Sketch the key actors and their connections (you don’t need complete data—use your intuition about who interacts with whom)

  2. Identify brokers: Who spans different groups? Who has access to diverse information sources?

  3. Identify closed clusters: Which groups have dense internal connections? Where might trust be highest?

  4. Strategic implications: Based on your analysis:

    • What are the risks if key brokers leave?
    • Where might silos be limiting information flow?
    • How could the network be restructured to improve performance?

Bring your analysis to class for discussion.

Ponder

Note🤔

Discussion Questions

1. The Closure-Brokerage Trade-off

Burt argues for the value of structural holes; Coleman emphasizes closure. Are these perspectives contradictory, or can they be reconciled? Consider: Under what conditions would you advise an actor to invest in bridging ties vs. strengthening existing relationships?

2. Dark Sides of Social Capital

Both closure and brokerage have potential downsides:

  • Closed networks can become insular, resistant to change, and exclusionary
  • Brokers may exploit information asymmetries or face burnout from bridging demands

How should organizations manage these risks while capturing network value?

3. Network Position and Ethics

The RBC fraud detection case shows how network analysis can identify criminal behavior. But similar techniques could be used to:

  • Identify union organizers or whistleblowers
  • Target vulnerable individuals for manipulation
  • Reinforce existing power imbalances

What ethical guidelines should govern the use of network analytics in organizations?

4. Building Your Network Strategically

Based on this week’s material, how would you approach building your own professional network? Should you focus on:

  • Deepening existing relationships (closure)?
  • Reaching out to new, distant contacts (brokerage)?
  • Some combination depending on context?

Core Readings

  • Structural Holes: Burt, R. S. (1992). Structural Holes: The Social Structure of Competition. Harvard University Press.

  • Social Capital: Coleman, J. S. (1988). “Social Capital in the Creation of Human Capital.” American Journal of Sociology.

  • Weak Ties: Granovetter, M. S. (1973). “The Strength of Weak Ties.” American Journal of Sociology.

Supplementary Readings

  • Good Ideas: Burt, R. S. (2004). “Structural Holes and Good Ideas.” American Journal of Sociology.

  • Brokerage and Closure: Burt, R. S. (2005). Brokerage and Closure: An Introduction to Social Capital. Oxford University Press.

  • Network Effects on Careers: Seibert, S. E., Kraimer, M. L., & Liden, R. C. (2001). “A Social Capital Theory of Career Success.” Academy of Management Journal.

  • Board Interlocks: Mizruchi, M. S. (1996). “What Do Interlocks Do?” Annual Review of Sociology.

Additional Resources

Tip🔧 Tools and Methods

Measuring Closure:

  • igraph::transitivity() — local and global clustering coefficients
  • igraph::triangles() — count triangles for each node

Measuring Brokerage:

  • igraph::betweenness() — betweenness centrality
  • igraph::constraint() — Burt’s network constraint (inverse of structural hole access)

Visualization:

  • Color nodes by constraint level to show brokerage positions
  • Use edge bundling to reveal community structure
  • Size nodes by betweenness to highlight bridges

Python alternatives:

  • networkx.clustering() — clustering coefficients
  • networkx.betweenness_centrality() — betweenness
  • networkx.constraint() — Burt’s constraint (available via custom implementation)