Exploring collaboration patterns across 192 scholars and 225 research connections
Scholars in Network
Collaboration Edges
Total Citations
Research Communities
Network Modularity
Avg Citations/Author
This analysis examines the structure and characteristics of my coauthor network, spanning 192 scholars across leading research institutions worldwide. Using network analysis and bibliometric methods, we uncover patterns of collaboration, identify key researchers, and map research communities in economics and related fields.
The network exhibits remarkably high modularity (0.734), indicating well-defined research communities centered around distinct areas: education economics, experimental/behavioral economics, development economics, and labor economics. Despite this clustering, the network remains fully connected with me serving as a primary bridge between communities (betweenness centrality: 0.763).
The network follows a power-law-like distribution typical of academic collaboration networks, with most authors having few connections while a small number of highly connected authors serve as hubs.
Average degree: 2.34 | Median: 1 | Max: 24 | The log-log plot (right) suggests scale-free network properties.
Citation counts reveal the scholarly impact across the network, with a highly skewed distribution reflecting the concentration of citations among top researchers.
| Rank | Author | Citations | Institution | Depth | Research Field |
|---|
Authors are categorized by their distance from me (the seed node): direct coauthors (depth 1) and coauthors-of-coauthors (depth 2). The majority (88%) are at depth 2, reflecting the network's breadth.
The network spans top research universities worldwide, with strong representation from Harvard, University of Chicago, Yale, Berkeley, and leading international institutions.
Strong positive correlations exist between citation counts, article productivity, and network position, suggesting that well-connected authors tend to be more productive and highly cited.
Using the Louvain algorithm, we identified 11 distinct research communities within the network. These communities reflect different research areas and institutional clusters.
Top Scholars:
Focus: Education policy, school choice, college access
Top Scholars:
Focus: Behavioral economics, replication, experimental methods
Top Scholars:
Focus: Economic development, institutions, growth
My position in the network serves as a critical bridge connecting these distinct research communities, with the highest betweenness centrality (0.763). This central position facilitates knowledge transfer and collaboration across traditional disciplinary boundaries, particularly linking education economics with broader labor and development economics research.
Data Collection:
Analysis Methods:
All analysis code, data, and visualizations are available for download and replication.
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