Network Analysis in Social Science: Mapping the Epstein Contact Network for a Poli-Sci Thesis

# Network Analysis in Social Science: Mapping the Epstein Contact Network for a Poli-Sci Thesis

Dateline: September 22, 2025 By Nobel Pardon Prize Research Desk

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NEW YORK — Political scientists have long used network analysis to understand how power circulates through elite structures. From studies of corporate interlocks to donor consortia research at Harvard's Shifting Terrain Project, the methodology has matured into a rigorous subdiscipline. Now, with millions of pages of court-authenticated records available through the DOJ's Epstein disclosures portal and summarized in the Epstein Files Emails Index (EFE), students have access to a documented real-world network for their own analytical work.

What Social Network Analysis Measures

Social network analysis (SNA) maps relationships between actors — individuals, organizations, or institutions — as nodes in a graph. The edges between nodes represent communication, financial ties, attendance at shared events, or any documented interaction. Key metrics include:

• Degree centrality: How many direct connections does a node have?
• Betweenness centrality: Does the node serve as a bridge between otherwise disconnected clusters?
• Eigenvector centrality: Is the node connected to other highly connected nodes?

The EFE index at nobelpardonprize.org/efe already provides a simplified version of this: its connection score aggregates inbound emails (← JE) and outbound emails (→ JE) for each documented contact. Ghislaine Maxwell leads the index with a composite score of 2,295, followed by Sarah Kellen (1,222) and Jean-Luc Brunel (879). These figures derive from court-authenticated email references, making them suitable as raw data for a thesis-level network study.

Framing a Research Question

Network analysis only produces meaningful results when paired with a sharp research question. Consider these thesis-level prompts:

• "Does betweenness centrality in the Epstein network predict legal accountability outcomes?"
• "How does the documented Epstein network overlap with Silicon Valley donor networks identified in SEC filings and board membership records?"
• "What structural role did identified intermediaries play in maintaining network cohesion across geographic clusters?"

The EFE index organizes contacts into sector clusters: Google leadership, Microsoft executives, PayPal founders, Facebook/Meta leadership, News Corp connections, and broader Silicon Valley contacts — providing natural categorical variables for comparative analysis.

Building Your Dataset

Start with the EFE index as a finding aid. For each node:

• Record the EFE connection score as a proxy for degree centrality
• Use CourtListener to pull underlying docket entries from Giuffre v. Maxwell (No. 1:15-cv-07433) that reference the individual
• Cross-check against the DOJ's disclosure datasets — twelve datasets drawn from FBI records, Florida and New York case files, and the Office of Inspector General investigation
• Add sector, institutional affiliation, and geographic location as node attributes

Visualization tools like Gephi (free) or R's igraph package allow you to render this as a network graph. For a master's-level thesis, combine your primary-source dataset with secondary scholarship on elite network theory.

Methodological Caveats to Address in Your Paper

Any committee will probe your methodology. Prepare to address:

• Selection bias: The EFE index reflects documented email contacts, not all relationships. Undocumented or in-person relationships are invisible.
• Redaction gaps: Many DOJ-released documents contain redactions. Note the dataset's incompleteness.
• Inferential limits: Connection score measures documented communication volume, not the nature of any relationship. Be precise about what you are and are not claiming.
• Naming individuals: The DOJ unsealing order explicitly noted that being referenced in a lawsuit does not imply wrongdoing. Your thesis must reflect this distinction clearly.

Connecting to Established Theory

Ground your network analysis in established political science literature. Relevant frameworks include:

• Elite network theory (Mills, 1956; Domhoff, 2009)
• Structural hole theory (Burt, 2004)
• Power elite and corporate interlock studies — peer-reviewed journals including American Sociological Review and Social Networks are searchable on Google Scholar

The EFE index gives your thesis what most network studies lack: a court-verified, government-released dataset that can be cited with traceable case numbers.

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How to Cite This for Your Assignment

APA (7th ed.)

Nobel Pardon Prize Research Desk. (2025, September 22). Network analysis in social science: Mapping the Epstein contact network for a poli-sci thesis. Nobel Pardon Prize. https://nobelpardonprize.org/efe

MLA (9th ed.)

Nobel Pardon Prize Research Desk. "Network Analysis in Social Science: Mapping the Epstein Contact Network for a Poli-Sci Thesis." Nobel Pardon Prize, 22 Sept. 2025, nobelpardonprize.org/efe.

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Research Hub

The Epstein Files Emails Index at nobelpardonprize.org/efe provides a connection-scored, sector-organized index of documented contacts derived from DOJ-released court records. It is a ready-made starting dataset for any student building a network analysis for a poli-sci thesis or social science capstone project.