About the project.

SH

Shouqi Han

Author · Sole investigator

Shouqi Han is the author and sole investigator of the AI Deal Network research project, which develops formal tools for measuring circular flows of capital, compute, and equity in concentrated technology markets. The project is independent and not affiliated with any firm in the sample.

Prior work spans network economics, financial-market microstructure, and the empirical analysis of corporate disclosure. The current paper is the first publication in a planned working-paper series on infrastructure-led market structure.

Affiliation
Independent
Field
Network economics, market structure
First paper
WP–2026.01 · May 2026

§ 1About this project

AI Deal Network is the companion site for a working paper that introduces three quantitative metrics for circularity in corporate ecosystems. Its purpose is twofold: to make the paper's data and case studies accessible to non-academic readers, and to serve as an open replication surface for researchers and journalists who wish to extend or contest the analysis.

The site is intentionally structured like a working paper. The home page summarises findings; the research section reproduces the paper in full; the methodology section provides the long-form technical companion; the case studies decompose individual cycles; the explore page exposes the raw network for inspection.

§ 2Acknowledgements

The project benefited from comments, data leads, and review from a number of readers whose contributions did not constitute an endorsement of any of its conclusions.

Data sources

SEC EDGAR · audited 10-K and 10-Q filings · firm press releases · contemporaneous reporting in major financial outlets.

Tools

NetworkX for graph algorithms · pandas for data wrangling · Observable for prototype visualisations · this site is hand-coded HTML.

Review

Pre-publication review provided by anonymous readers in the network-economics community. Remaining errors are the author's alone.

Disclosures

The author holds no equity in any firm in the sample and has no consulting or paid advisory relationship with any of them.

§ 3Contact

Corrections, additions, and replication notes are welcome. The fastest channel is email.

§ 4Citation & license

The paper is released under CC BY-NC 4.0. Code and sample data are released under MIT. Standard academic citation is appreciated; the canonical form appears in the research section.