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Table 1 Statistics of single-layer networks and the aggregated (AGG.) network, including 1. the number of active nodes N[α], i.e., nodes that are connected by at least one in-/out-link (Nicosia and Latora 2015); 2. the total number of edges E[α]; 3. the average strength 〈s[α]〉; 4. density D[α] measuring the ratio of the number of edges to maximum possible number of edges; 5. fraction of nodes in the giant weakly connected component %G[α]; 6. reciprocity r[α] quantifying the likelihood of nodes with mutual links; 7. the Kendall’s τ correlation between in- and out-strengths \(\tau \left (s_{in}^{[\alpha ]}, s_{out}^{[\alpha ]}\right)\). 8. global clustering coefficient C[α] which measures the extent that two neighbors of a node are connected; 9. assortativity coefficient by strength \(A_{s}^{[\alpha ]}\), i.e., the correlation between the out-strengths of source nodes and the in-strengths of destination nodes (Newman 2003)

From: Characterizing dynamic communication in online eating disorder communities: a multiplex network approach

Network

Mental

Social

Fitness

Body

Thinspo

AGG. (all αs)

N [ α]

9381

28,959

17,689

11,199

14,156

55,164

E [ α]

17,306

54,609

34,040

17,881

27,807

140,330

〈s[α]〉

3.55

2.89

2.94

2.46

2.96

4.32

D [ α]

1.97 ×10−4

6.51 ×10−5

1.09 ×10−4

1.43 ×10−4

1.39 ×10−4

4.61 ×10−5

% G [ α]

76.55%

89.17%

83.84%

73.87%

88.87%

95.67%

r [ α]

0.24

0.19

0.36

0.45

0.33

0.29

\(\tau \left (s_{in}^{[\alpha ]}, s_{out}^{[\alpha ]}\right)\)

-0.06

-0.04

0.09

0.21

0.13

0.11

C [ α]

0.06

0.04

0.03

0.03

0.01

0.03

z(C[α])

40.70

198.96

61.25

109.21

6.29

160.67

\(A_{s}^{[\alpha ]}\)

-0.08

-0.07

-0.1

-0.02

-0.08

-0.1

\(z\left (A_{s}^{[\alpha ]}\right)\)

-10.64

-17.24

-19.05

-4.60

-14.04

-37.80

  1. Values of z(x) are z-scores for the empirical results based on null models. For each property x of a network, we generate 1000 randomized networks via the configuration model (Newman and Girvan 2004) and measure the property in these randomized networks. Then, the deviation of x from randomness is quantified by a z-score: z(x)=(x−〈x〉)/σx, where 〈x〉 is the mean value of the property in randomized networks and σx is the standard deviation