Paul Sweezy’s Corporate Interest Groups Revisited

Tom Mills

Paul Sweezy’s Corporate Interest Groups Revisited

Tom Mills

Research output: Other contribution › Blog Post

Abstract

In this post I revisit pioneering work by the American Marxist economist Paul Sweezy in which he examined a network of the largest US companies in 1935, identifying eight distinct ‘interest groups’ based on common control. I compare Sweezy’s groups to the results of a consensus-based community detection algorithm.

Original language	English
Publication status	Published - 21 Apr 2026

Keywords

intellectual history
elites
network analysis
capital
computational social science

Cite this

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title = "Paul Sweezy{\textquoteright}s Corporate Interest Groups Revisited",

abstract = "In this post I revisit pioneering work by the American Marxist economist Paul Sweezy in which he examined a network of the largest US companies in 1935, identifying eight distinct {\textquoteleft}interest groups{\textquoteright} based on common control. I compare Sweezy{\textquoteright}s groups to the results of a consensus-based community detection algorithm.",

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N2 - In this post I revisit pioneering work by the American Marxist economist Paul Sweezy in which he examined a network of the largest US companies in 1935, identifying eight distinct ‘interest groups’ based on common control. I compare Sweezy’s groups to the results of a consensus-based community detection algorithm.

AB - In this post I revisit pioneering work by the American Marxist economist Paul Sweezy in which he examined a network of the largest US companies in 1935, identifying eight distinct ‘interest groups’ based on common control. I compare Sweezy’s groups to the results of a consensus-based community detection algorithm.

KW - intellectual history

KW - elites

KW - network analysis

KW - capital

KW - computational social science

UR - https://tamills1981.github.io/society-from-the-top-down/posts/sweezy-interest-groups/

M3 - Blog Post

ER -

Paul Sweezy’s Corporate Interest Groups Revisited

Abstract

Keywords

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