The CORPNET research group uncovers, investigates and aims to understand global networks of corporate power in contemporary global capitalism

What are we doing?

Data collection

• Macro-data: e.g. Country indicators
• Micro-data: Surveys

• Linear regression

• By hand in Excel

"standard" social science framework

Data wrangling

Data

analysis

(2) Modeling data-missingness

(6) Non-linear modeling

(4) Machine learning:

• Database merging
• Data classification

computational social science framework

Data collection

(1) New methods to collect data: Data scraping

Data wrangling

Data

analysis

(3) Set up appropriate data structures

(7) Motif-detection

(5) Description (data viz)

(1) New methods to collect data: Data scraping

(2) Modeling data-missingness

(3) Set up appropriate data structures

(4) Machine learning:

• Database merging
• Data classification

(5) Description (data viz)

(6) Motif-detection

(7) Non-linear modeling

1. Ising model to understand information spread across the network of interlocks (w/ Rick Quax)
2. Higher-order markov chains to understand combinations of countries that are important
3. SBM to predict the tax rate using corporate networks (w/ Leto Peel)

...however this is our weaker part. Most of our research is descriptive.

https://CSSamsterdam.github.io/