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Applied Network Science

Table 1 Empirical networks Structural properties of five real-world networks: Escorts, Swarthmore42, Caltech36, Wikipedia, and GitHub

From: Explaining classification performance and bias via network structure and sampling technique

Dataset

Escorts

Swarth.

Caltech

Wiki.

GitHub

N

16730

1519

701

2132

37700

m

1

1

1

1

1

class

role

gender

gender

gender

dev

minority

escort

2 (m)

1 (f)

female

1 (ML)

B

0.40

0.49

0.33

0.15

0.26

E

39044

53726

15464

3143

289003

d

0.0003

0.05

0.06

0.001

0.0004

\(\beta\)

2.87

5.50

4.90

2.87

2.54

H

0.00

0.52

0.54

0.64

0.84

\(N_{fit}\)

14338

208

179

2893

9830

\(m_{fit}\)

2

2

2

2

2

  1. In addition to the properties of interest, we report \(\beta\), the power-law exponent of the degree distribution computed as described in Karimi et al. (2018). \(N_{fit}\) and \(m_{fit}\) represent the number of nodes and minimum degree utilized to generate synthetic networks, respectively
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