Table 5 List of features used in the prediction of a directed link between generic users u and  v , along with their description

Location

Binary attribute, whether u and v belong to the same city

14

Gender

Binary attribute, whether u and v belong to the same gender

15

Age

Absolute difference of ages

12

Library

Cosine similarity between library vectors

5

Groups

Cosine similarity between group membership vectors

7

Group size

Size of the smallest group the two users have in common

6

Vocabulary

Cosine similarity between sets of tags used

16

Contact list

Cosine similarity of the vectors of social contacts

2

Outdegree

Sum of the out degrees ($k_{\mathrm{out}}(u)+k_{\mathrm{out}}(v)$)

11

Preferential attachment

Product of the out degrees ($k_{\mathrm{out}}(u)\cdot k_{\mathrm{out}}(v)$)

13

Common neighbors

Number of common neighbors, directed case ($CN(u,v)=|{\mathrm{\Gamma }}_{\mathrm{out}}(u)\cap {\mathrm{\Gamma }}_{\mathrm{in}}(v)|$)

4

Triangle overlap

$\frac{CN(u,v)}{{\mathrm{\Gamma }}_{\mathrm{out}}(u)}$

1

Reciprocation

Binary attribute, whether the inverse link (v,u) is already present

9

Resource allocation

${\sum }_{z\in ({\mathrm{\Gamma }}_{\mathrm{out}}(u)\cap {\mathrm{\Gamma }}_{\mathrm{in}}(u))}(\frac{1}{k_{\mathrm{out}}(z)})$ [37]

3

Local path

Linear combination of common neighbors and common distance-2 neighbors ($CN+ϵ\cdot C{N}_2$) [37]

10

Weighted flow

$wf(u,v)=CN(u,v)+\frac{{\sum }_{x\in CN(u,v)}min(w(u,x),w(x,v))}{CN(u,v)}$

8