125
1 Professor Ernesto Estrada Department of Mathematics & Statistics University of Strathclyde Glasgow, UK www.estradalab.org

Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

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Page 1: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1

Professor Ernesto EstradaDepartment of Mathematics & Statistics

University of Strathclyde

Glasgow, UK

www.estradalab.org

Page 2: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

2

Page 3: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

3

Page 4: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Measure what is measurable, and make measurable what is not so.

Galileo Galilei

Page 5: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Professor Ernesto EstradaDepartment of Mathematics & Statistics

University of Strathclyde

Glasgow, UK

www.estradalab.org

Page 6: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

kkp ~ kkekp /~

!k

kekp

kk

2

2

2

2

1 k

kk

k

ekp

Page 7: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

kkp ~ !k

kekp

kk

Page 8: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Poisson

Exponential

Gamma

Power-law

Log-normal

Stretched exponential

Stumpf & Ingram, Europhys. Lett. 71 (2005) 152.

Page 9: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 10: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

kekp kk /~

2~

222//ln

k

ekp

mk

Stumpf & Ingram, Europhys. Lett. 71 (2005) 152.

Page 11: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 12: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 13: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 14: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

The qualitative interpretation of the skew is

complicated. For example, a zero value

indicates that the tails on both sides of the

mean balance out, which is the case for a

symmetric distribution, but is also true for an

asymmetric distribution where the asymmetries

even out, such as one tail being long but thin,

and the other being short but fat. Further, in

multimodal distributions and discrete

distributions, skewness is also difficult to

interpret. Importantly, the skewness does not

determine the relationship of mean and

median.

Wikipedia

Page 15: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

• Collatz-Sinogowitz Index (1957)

kGCS 1

• Bell Index (1992)

2

2 11

i

i

i

i kn

kn

GVar

• Albertson Index (1997)

Eji

ji kkGirr,

Unknown

upper

bounds

Page 16: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

i

ik

p1

ji

ijkk

p11

2

1

Estrada: Phys. Rev. E 82, 066102 (2010)

ji

ijkk

p1

ˆ

ijijij pp ˆ

Page 17: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

2

11

2112

ji

jiji

ij

kk

kkkk

Eij jiEij

ijkk

G

2

112

Page 18: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

AKL

otherwise,0

,~for 1

,for

ji

jik

L

i

ij

2/12/1

2/12/1

KAKI

KLKL

otherwise,0

,~for 1

,for 1

jikk

ji

ji

ijL

Page 19: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

.2

2

11

,

2/1

Gn

kkn

G

Eji

ji

T

L

Page 20: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

2

1n

Gn

12

2~

nn

GnG

0~1 G

Page 21: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

n 210

n

i

j

j

j

T

j in 1

1

1

1cos

j

jj

T nG 2cos11

L

j i

jj

T iG

2

11

L

Page 22: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

jjjx cos1

jjjy sin1

n

j

jxnn

nG

1

2

12

~

j

01

j

jx

jy

y

x

Page 23: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

8k 16k

pnG ,

017.0~ G 034.0~ G

Page 24: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1227.2

27.018.1

18.1

nn

n

k

kBA

8k 16k

132.0~ G 108.0~ G

Page 25: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 26: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

S. cereviciaeD. melanogaster

C. elegansH. pylori

148.0~ G 294.0~ G

E. coli

241.0~ G

323.0~ G 383.0~ G Stretched exponential

Log-normal

kekp kk /~

2~

222//ln

k

ekp

mk

Page 27: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Professor Ernesto EstradaDepartment of Mathematics & Statistics

University of Strathclyde

Glasgow, UK

www.estradalab.org

Page 28: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1,305 mi.

Stanley Milgram

1933-1984

Page 29: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

CLUSTERINGDISTANCE

Page 30: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

5ij

d

Page 31: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

i

iCi

node of relations e transitivpossible ofnumber total

node of relations e transitivofnumber

1

2

2/1

ii

i

ii

ii

kk

t

kk

tC

i

iCn

C1

Page 32: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

d 3.65

0.79

2.99

0.00027

1847

0.74C

Page 33: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

d 2.65

0.28

2.25

0.05

10.5

0.69C

33

Page 34: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

d 18.7

0.08

12.4

0.0005

926

0.3C

34

Page 35: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

D. J. Watts

S. H. Strogatz

35

Page 36: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

There is a high probability that the shortest path connecting nodes p and q goes through the most connected nodes of the network.

Sending the ‘information’ to the most connected nodes (hubs) of the network will increase the chances of reaching the target.

The sender does not know the global structure of the network!

36

Page 37: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

But also, there is a high probability that the most connected nodes of the network are involved in a high number of transitive relations.

Sending the ‘information’ to the most connected nodes (hubs) of the network will increase the chances of getting lost.

37

Page 38: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Definition: A route is a walk of length l, which is any sequence of (not necessarily different) nodes v1,…, vl such as for each i =1,…,l there is a link from vl to vl+1.

Definition: The communicability between two nodes in a network is defined as a function of the total number of routes connecting them, giving more importance to the shorter than to the longer ones.

38

Hypothesis: The information not only flows through the shortestpaths but by mean of any available route.

Page 39: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

39

0

# of walks in steps from to pq l

l

G c l p q

The between the nodes p and q is then mathematically defined as

where cl should:

makes the series convergent

gives more weight to the shorter than to the longer walks

Page 40: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

VpVp pfpfV

2

2

Eqp

qfpAf,

Definition: Let .

The adjacency operator is a bounded operator on

defined as .

Theorem: (Harary) The number of walks of length l

between the nodes p and q in a network is equal to .

pq

lA

V2

40

Page 41: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

The communicability function can be written as:

qjpj

l

j

l

n

j

lpq

l

l

lpq cAcG ,,

0 10

41

Let be a nonincreasing ordering

of the eigenvalues of A, and let be the eigenvector

associated with .

n 21

j

j

Page 42: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

42

jee

l

AG

n

j

qjpjpq

A

l

pq

l

pq

1

,,

0 !

n

j j

qjpj

pq

l

pq

ll

pq AIAG1

,,1

0 1

1

10

Page 43: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1 1

1 1

2

nn

pq n j j

j

G K p q e e p p

11

2

1 1 11 .

n n

pq n j j

j

nn

eG K e p p

n

ee

n ne ne

pq nG K

Page 44: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

2cos1

j

j

n

2sin

1 1j

jpp

n n

2cos

1

1

2cos1

1

2 2sin sin

1 1 1 1

2sin sin .

1 1 1

jnn

pq n

j

jnn

j

jp jqG P e

n n n n

jp jqe

n n n

Page 45: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

sin sin 1/ 2 cos cos

2cos 2cos

1 1

1

1 1cos cos

1 1 1 1

j jnn n

pq n

j

j p q j p qG P e e

n n n n

1,2, ,j n 1/ nj ,0

2cos 2cos

0 0

1 1cos cospq nG P p q e d p q e d

/ 1j n

Page 46: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

x cos

0

1cos e d I x

2 2pq n p q p qG P I I

1 1 12 2 0n n n nG P I I

Page 47: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 48: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

x

xx

xxx

x

x

xooo

oooo

ooo

0 5 10 15 20

0.4

0.3

0.2

0.1

0

-0.1

-0.2

-0.3

-0.4

-0.5

Subject

Second larg

est

princip

al valu

e

x

x

x

x

x

x

x

x

oooo o

oo

o

0 5 10 15 20

0.4

0.3

0.2

0.1

0

-0.1

-0.2

-0.3

-0.4

-0.5

x

oo

Subject

Second larg

est

princip

al valu

e

pqpq AWWG 2/12/1exp

~

Page 49: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

: Stroke : Decreased communicability

: Stroke : Increased communicability

Images courtesy of Dr. Jonathan J. Crofts.

Page 50: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Professor Ernesto EstradaDepartment of Mathematics & Statistics

University of Strathclyde

Glasgow, UK

www.estradalab.org

Page 51: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Local metrics provide a measurement of a structural

property of a single node

Designed to characterise

Functional role – what part does this node play in

system dynamics?

Structural importance – how important is this node to

the structural characteristics of the system?

Page 52: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

jee

l

AG

n

j

pjpp

A

l

pp

l

pp

1

2

,

0 !

1) 3.026

2) 1.641

3) 1.641

4) 3.127

5) 2.284

6) 2.284

7) 1.592

8) 1.592

1

2

3

4

5

6

7

8

Page 53: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1

2

3

4

56

7

8

9 8,6,5,3,11 S

65.451 SpGpp

9,7,4,22 S

70.452 SpGpp

Page 54: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Essential

54

Page 55: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

55

Rank Protein Essential

?

1 YCR035C Y

2 YIL062C Y

... ... ...

Page 56: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Estrada: Proteomics 6 (2009) 35-40

0

10

20

30

40

50

60

70P

erc

en

tage o

f E

ssen

tial P

rote

ins

Iden

tifi

ed

Page 57: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

57

Consider that two nodes p and q are trying to communicate with each other by sending information both ways through the network.

ppGQuantifies the amount of ‘information’ that is sent by p, wanders around the network, and returns to the origin, the node p.

pqGQuantifies the amount of ‘information’ that is sent by p, wanders around the network, and arrives to its destination, the node q.

We know that:

Page 58: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

2def

pq pp qq pqG G G

The goal of communication is to maximise the amount of information that arrives to its destination by minimising that which is lost.

58

Page 59: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Theorem: The function is a Euclidean distance. pq

59

T

pq p q p qe Λφ φ φ φ

1

2

0 0

0 0

0 0 n

Λ

1

2

p

n

p

p

p

φ

Proof:

Page 60: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

60

/2 /2

/2 /2 /2 /2

2

T

pq p q p q

T

p q p q

T

p q p q

p q

e e

e e e e

Λ Λ

Λ Λ Λ Λ

φ φ φ φ

φ φ φ φ

x x x x

x x

Proof (cont.):

Page 61: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

61

pqpqd

p q

Page 62: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

62

p q

1P

p q

2P

09.5

1,,

2/1

PjiEji

ij

80.4

2,,

2/1

PjiEji

ij

Remark. The shortest route based on the communicability

distance is the shortest path that avoids the nodes with the

highest ‘cliquishness’ in the graph.

Page 63: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 64: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

81.56 10 83.30 10

Page 65: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Fraction of nodes

removed

Page 66: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

The routes minimizing the communicability distance are the shortest ones

that avoid the hubs of the network. Then, they can be useful to avoid

possible collapse of the networks due to the removal of the hubs.

Page 67: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

67

Essential

Page 68: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

q

qp

n

,

1

q

qpd

n

,

1

68

Page 69: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

69

large ppG

Wikipedia

Page 70: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

70

qqpp

pqdef

pqGG

G

Theorem. The function is the cosine of the Euclidean

angle spanned by the position vectors of the nodes p and q.

pq

qqpp

pq

qp

qp

pqGG

G

xx

xx11 coscos

Definition:

Page 71: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

71

a

bcR

2

2 2

4

1

11

AT ea 1 AT esb sesc AT

Theorem. The communicability distance induces an

embedding of a network into an (n-1)-dimensional

Euclidean sphere of radius:

Estrada et al.: Discrete Appl. Math. 176 (2014) 53-77.

Estrada & Hatano, SIAM Rev. (2016) in press.

ATT essC 211 Aediags

Remark. The communicability distance matrix C is circum-

Euclidean:

Page 72: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

72

2/1

2/1

2/1

1

2/1

0

2/1

2

2/1

2/1

2/1

3

jjjA

Page 73: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

73

0.08.06.0

0.0

7.0

0.0

0.1

0.1

xy

z

2

3

1

0.00.1

2

3

1

0.1

0.1

Page 74: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

74

2

1

3

x

y

z

0.1

0.0

0.1

0.10.1

0.0

0.10.2

0.0

O

1x

2x

3x

Page 75: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

75

px

qx

O

ppp Gx pq

pq

qqq Gx

Estrada & Hatano: Arxiv (2014) 1412.7388.

Estrada: Lin. Alg. Appl. 436 (2012) 4317-4328.

qppq xxG

Page 76: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Professor Ernesto EstradaDepartment of Mathematics & Statistics

University of Strathclyde

Glasgow, UK

www.estradalab.org

Page 77: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1V 2V

1 2V V V

0

0T

BA

B

1j n j

Page 78: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 79: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

m

mb

fr1

Problem:

Page 80: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

sinh 0Bipartivity Tr A

Bipartivity No odd cycles

Page 81: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

exp sinh coshTr A Tr A Tr A

exp coshBipartivity Tr A Tr A

EE

EE

ATr

ATrb even

n

j

j

n

j

j

s

1

1

exp

cosh

exp

cosh

Page 82: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

even evens s

EE EE ab G b G e

EE EE a b

Theorem.

G G e

e

b

a

Page 83: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1.000sb 0.829sb 0.769sb 0.721sb

0.692sb 0.645sb 0.645sb 0.597sb

Page 84: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1 1

1 1

cosh sinh

cosh sinh

n n

j j

j j

e n n

j j

j j

b

1

1

expexp

expexp

n

j

j

e n

j

j

Tr Ab

Tr A

Page 85: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1.000sb 0.658sb 0.538sb 0.462sb

0.383sb 0.289sb 0.289sb 0.194sb

Page 86: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Hervibores

Grass

Parasitoids

Hyper-hyper-parasitoids

Hyper-parasitoids

0.766sb

0.532eb

Page 87: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 88: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 89: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

j = 1 j = 2 j = 3

j = 4 j = 5 j = 6

Page 90: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

ˆ exp cosh sinhpq pq pqG A A A

ˆ sinh 0pq pqG A

p

q

p

q

ˆ cosh 0pq pqG A

0 and in different partitionsˆ 0 and in the same partitions

pq

p qG

p q

Page 91: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1

3

7

4

6

10

8

11

9

12

5

2

Page 92: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

38.919.872.673.680.636.628.777.610.705.704.773.8

19.81.1083.609.711.766.673.862.598.729.728.702.9

72.683.603.817.487.543.504.731.632.456.665.528.7

73.609.717.405.862.550.505.742.562.630.456.629.7

80.611.787.562.517.893.310.768.596.562.632.498.7

36.666.643.550.593.337.777.639.568.542.531.662.5

28.773.804.705.710.777.638.936.680.673.672.619.8

77.662.531.642.568.539.536.637.793.350.543,566.6

10.798.732.462.696.568.580.693.317.862.587.511.7

05.729.756.630.462.642.573.650.562.505.817.409.7

04.728.765.556.632.431.672.643.587.517.403.883.6

73.802.928.729.798.75.6219.866.611.709.783.61.10

G

Page 93: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

011111000000

101111000000

110111000000

111011000000

111101000000

111110000000

000000011111

000000101111

000000110111

000000111011

000000111101

000000111110

~G

Page 94: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

10

12

11

8

7

9

2

3

4

1

5

6

1 1,2,3,4,5,6C

2 6,7,8,9,10,11,12C

1

3

7

4

6

10

8

11

9

12

5

2

Page 95: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

2 3

10

4

1211

1 5 6

87 91

3

7

4

6

10

8

11

9

12

5

2

Page 96: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 97: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 98: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Professor Ernesto EstradaDepartment of Mathematics & Statistics

University of Strathclyde

Glasgow, UK

www.estradalab.org

Page 99: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

VS VS 2/1

S

Let and

represents the number

of edges with exactly one

endpoint in S.

12

min , ,02n

S

S VG S V S

S

Page 100: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1 21 1 22

2G

N 321(Alon-Milman): Let

21

Page 101: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

A Ramanujan graph

n = 80, = 1/4

The Petersen graph

n = 10, = 1

Page 102: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

S S

SS

bottleneck

Page 103: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 104: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

MySQL 30.7

93.6 56.5

St Marks St Martin

Page 105: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

t

t

t

t

Page 106: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

iiG

i

800,628,3321

!

1032

0

iiiiii

k

ii

k

ii

AAA

k

AG

Page 107: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

i i

i

1/2 1/6

1/24i

1/40320

Page 108: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

iNk

1

1

n

j

kkk jNiNis

i,1

Page 109: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

k

jpj

n

p

n

j

ijk iN ,

1 1

,

n

p

k

jqj

n

q

n

j

pj

n

p

k pN1

,

1 1

,

1

n

p

k

jqj

n

q

n

j

pj

k

jpj

n

p

n

j

ij

k is

1

,

1 1

,

,

1 1

,

Page 110: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

.

1 1

,1,1

1

,1,1

1 1

1,1,1

1

1,1,1

n

p

n

q

qp

n

p

pi

n

p

n

q

k

qp

n

p

k

pi

k is

2

1

,1

1 1

,1,1

n

j

p

n

p

n

q

qp in

p

p

i

k is ,1

1

,1

,1

k

Remark: The eigenvector centrality of a given node represents the probability of selecting at random a walk of infinite length that hasstarted at that node.

Page 111: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

1 2

n

j

jijiiiG2

2

,1

2

,1 expexp

1

2

,1 exp iiiG

2ln

2

1ln 1

,1

iii G

i,1ln

iiGln

Page 112: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 113: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 114: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

5.0

1

2

,1

,1

explnln

ii

i

iG

Page 115: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

iiii GVi 1

2

,1,1 exp,0ln

Page 116: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

iiii GVi 1

2

,1,1 exp,0ln

Page 117: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

iiii GVi 1

2

,1,1 exp,0ln

Page 118: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

andVpp ,0ln ,1Vqq ,0ln ,1

Page 119: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 120: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 121: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 122: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

Chordless cycle

of length 15

Page 123: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada
Page 124: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada

MySQL

3105.1

St Marks St Martin

31090.2

67.1

Page 125: Traditional vs Nontraditional Methods for Network Analytics - Ernesto Estrada