Transcript Collaborative Research Network: Case Study at Molde

In765 Knowledge Networks:
A Structural Study of Networks
Judith Molka-Danielsen
Molde University College
[email protected]
http://home.himolde.no/~molka
2005
Types of Networks..
Social
Networks
Friends, families,
colleagues
Logical
web-pages,
Resources P2P-Gnutella
Physical
Internet
Resources IP routers
Transport Roads, railroads,
airline, electricity
Telephone Wireline, mobile
Economic Firms, markets,
organization
Why Study Networks?
Research Areas
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Availability and vulnerability of services:
electric, telephone, air connections, etc.
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Preventing or stopping of viruses on data
networks.
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The importance of weak ties: connectivness
to the core, finding a job, finding a web
page.
The characterization of network structure
and the role of hubs in the spreading an
idea, or proliferation of a product, and
managing organizations.
Former Research
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Random Network Theory –Erdös & Rényi (1960)
Six Degrees of Separation –S.Milgram (1967)
Cluster Coefficient –Small Worlds – Watts &
Strogatz (1998)
Hubs and Scale Free Networks – Albert, Jeong, &
Barabási (1999)
Hubs in Social Networks – Malcolm Gladwell
(2000)
Random Networks
Erdös-Rényi model
(1960)
Connect with
probability p
p=1/6
N=10
k ~ 1.5
- Democratic
- Random
Pál Erdös
(1913-1996)
Poisson distribution
Six Degrees of
Separation
Nodes: individuals
Links: social relationship
(family/work/friendship/etc.)
S. Milgram (1967)
John Guare (1980)
Six Degrees of Separation
Social networks: Many individuals with diverse
social interactions between them.
Cluster Coefficient
Clustering: My friends will likely know each other!
Probability to be connected C
»p
# of links between 1,2,…n neighbors
C=
n(n-1)/2
Cfriends= 15/ [6(5)/2] = 100%
Network
C
Crand
L
N
WWW
0.1078
0.00023
3.1
153127
Internet
0.18-0.3
0.001
3.7-3.76
30156209
Actor
0.79
0.00027
3.65
225226
Coauthorship
0.43
0.00018
5.9
52909
Metabolic
0.32
0.026
2.9
282
Foodweb
0.22
0.06
2.43
134
C. elegance
0.28
0.05
2.65
282
Hubs in Networks
200 million
searches each day
 More than 2300
searches per
second
 In 88 languages
 3.2 billion web
pages indexed.
 10 000 super
computers perform
the searches.

Do we find Hubs in Social Networks? Yes.
Most influencial
 Access to the most information
 Impacts others decisions most
 Have the most power

Who do you know?
(similar to a study by Malcolm Gladwell, 2000)
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Bjørnstjerne Bjørnsons Vei
Alme Jørund
Andenes Aud
Andestad Reidar
Bakke Gerd Inger
Bergseth Egil
Bergtun Lill Eldrid
Bjøringsøy Karl Magnar
Bjørkly Jorunn
Bjørkly Åsa Bjordal
Bjørnebo Solveig Randi Midtbø
Broks Vivi-Annie
Brokstad Jon
Drageseth Dagfinn
Dyrli Janne Merete
Døving Ellen
Eilertsen Gudny
Flø Jorunn Marie
Fylling Lars Kristen Tovan
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Gjære Arne
Gjære Guro Wiersholm
Gjære Vibeke Wiersholm
Grønbugt Rutt
Grønset Erling Rune
Gudbrandsen Åste Einbu
Gøncz Geir Janos
Göncz Arne
Hansen Helge
Hansen Sissel
Helde Marit Illøkken
Henriksen Line
Hjelmsøt Maria
Hoem Jermund
Hofset Siv
Jenset Grete
Jenset Torbjørn
Jordet Birgit
Kanestrøm Andreas Julshamn
…
Who do you know?: survey to faculty
B
A = number of persons known on the list.
15
1
10
1
9
1
8
1
6
B = number of persons (nodes) that person A knows.
A
Power Law Distribution of Node Linkages
B
2
1215
1
12
5
2
8-11
3
10
3
1
4
5
8
2
4-7
1
6
0
3
0-3
13
gruppert
6
22
14
4
2
0
0-3
4-7
8-11
Number of Links
12-15
Number of Nodes
A
No of nodes
Who do you know?: survey to students
A = number of persons known on the list.
B
23
1
14
1
6
1
5
1
4
4
3
1
2
3
1
16
0
20
48
B = number of persons (nodes) that person A knows.
A
Power Law Distribution of Node Linkages
B
40
1523
1
7-14
1
25
5-6
2
20
2-4
8
10
0-1
36
gruppert
35
30
15
5
0
0-1
2-4
5-6
Number of Links
7-14
15-23
Number of Nodes
A
Scale Free Networks and Power Laws
by Albert, Jeong, Barabasi.
Collaboration Among Researchers
Networks have diverse nodes and links are
-computers
-phone lines
-routers
-TV cables
-satellites
-EM waves
-researchers
-co-authorship
Unique co-author link distribution –
researchers represented individually
#Researchers - with exactly this count
Unique Co-authors Distribution
14
12
10
8
6
4
2
0
0
20
40
60
#Unique Co-author Links
80
Unique Co-Authors versus Publications
# Unique Co-Authors
Unique Co-Authors vs. Publications
70
60
50
40
30
20
10
0
0
50
100
150
Number of Publications
200
250
Average # of Co-Authors versus Publications
Average # of Co-Authors
Average #Co-Authors vs # Publication
4,50
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
Number of Publications
200
250
K.Haugen
7
2
17
P. Sætre
K.Haugen
e
l ac
S.W
al
Informatics
J.Odeck
5
2
A.Olstad
2
K.Jörnsten
4
11
NJ.Berland
77
2
17
1
H. Arntzen 2
2 Ø.Halskau
A. Løkketangen
47
all
a
ce
15
K. Danielsen
8
1
1
6
4
25
26
J.Molka-Danielsen
1
10
5
1
6
1
10
A-K Wallace
1
Olstad
5
D. Tipper
B. Jæger
K.Haugen
4
6
LM Hvattum
15
6
1
O. Ohren
7
J.Odeck
3
17
D. Woodruff
2
1
O. Bø
16
S.
W
K.A. Olsen
M.Spring
O.Larsen
HF Nordhaug
4
2
R. Hveberg
ce
1
AG
14
Li
um
K.Borgen
2
F.Løbersli
S.
W
al
la
M.Risnes
2
T.Crainic
Informatics Institute Cluster: researchers and co-author links
2
n
th
e
3
rv
He
.
A
S.
Br
å
T.Aarseth 5
I.Gjerde4
ik1
Helsefag
3
E.Jørgensen
30
Å.Brekk1
22
D.M.Berge
O.Hauge1
æter
H. Gammels
6
ø
R
L.
4
M.Løvlien
K.Westad Hauge
o
nh
e
vd
5
1
E.Lykkeslet Strømskag
2
1
4
E.Braute
4
R. Michaelsen
1
1
3
4
J. Berg
2
52
20
1
4
G-U.Stavik
S. Bjørkly
S. Vatne
2
T.Skrondal
1
1
T.Aarseth
I.Gjerde 1
3
H.Sundal
1
E. Rekdal
H.
er
lsæt
e
m
Gam
1
HK.Aass
1
AM.Botslangen
2
K.Dahl
1
2
H.Bakken
2
AJ.Orøy
2
I.Kamsvåg
2
A.Ødegård
Health Institute Cluster:
researchers and co-author links
A. Hervik
E.Rekdal
Samfunnsfag
S. Vatne
3
3
N.Rudi
16
1
1
1
EG.Standal
1
E.Rekdal
1
3
Ø.Opdal
4
B.Jákupsstovu
80
2
DM Berge 1
5
A.Brekk
A. Hervik
H. Gammelsæter
1
31
1
2
T. Aarseth
6
9
1
H.Bakken
Berg
D.M.
I. Gjerde
3
1
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akk
B
.
H
3
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4
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n
28
2
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rg
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.
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K. Tornes
e
D
2
rg
Be
.
D.M
e
D.M.Berge 6
Social Sciences Institute:
researchers and co-author links
Økonomi/Logistikk
K. Haugen
4
5
A.Løkketangen
2
20
1
2
2
Dauzère-Pérès
5
237
S. Wallace
2
7
A.Olstad
1
1
O.Larsen
A.Løkketangen
AK.Wallace
A.Hervik
ik
vi k
39
D.Woodruff
1
A.H
er
NJ.Berland 2
1
A.
A.
H
S.
Br
å
11
2
vik
Her
er v
en
th
2
1
D.Woodruff
rland
7 NJ.Be
A.Løkketangen 2
ic
T.Crain
2
2
4
2
2
A.Løkketangen
2
T.Crainic
30
2
3
Ø. Halskau
K.Jörnsten
7
1
9
I.Gribkovskaia
1
2
3
AG.Lium
1
98
2
A.Hervik
69
A.Buvik
4 A.Løkketangen
Economics/Logistics Cluster: researchers and co-author links
5
B.Guvag
Økonomi
2
R.Rasmussen
13
B. Foss
4
er ge
DM-B
3
2
11
K.Bedringås
19
5
88
P. Solibakke
4
O.Sættem
S. Bråthen
13
D. Woodruff 3
19
J.Odeck
2
A.Løkketangen
14
2
8
154
26
1
A.Hervik
H.Hjelle
1
DM-Be
r ge 1
Ø. O
6
A.Dedekam
3
1
p da
l3
1
1
DM-Berge
9
1
H.G
O.Hauge
am
me
ls
3
12
H.Bremnes
O. L a r s
en
2
S.Wallace
1
2
A.Olstad
1
A.Buvik
æte
r
1-S.Vatne
1-Ø.Opdal
2
K.Jörnsten
11
K.Haugen
2
E.Rekdal
1-H.Gammelsæter
Economics Institute Cluster: researchers and co-author links
1
2
E.Rekdal
12 3
H.Bremnes
1
2
1
Informatics
39
K. Haugen
4
Økonomi/Logistikk
2
20
2
O.Larsen
5
237
S. Wallace
2
1
5
7
A.Olstad
1
2
2
4
4
2
30
3
Ø. Halskau
7
9 1
1
I.Gribkovskaia
2
3
1
AG.Lium
2
69
A.Buvik
98
K.Jörnsten
2
28
K. Tornes
3
2
4
1
2
4
80
5
1
30
D.M.Berge
1
1
2
3
6
2
11
L.Rønhovde
2
2
1
1
1
1
2 6
9
I. Gjerde
3
4
7
K.Borgen
1
1
A.Brekk
3
9 3 1
O.Hauge
7 11
26
H.Hjelle
1
1
31
T. Aarseth
1
5
10
154
A.Hervik
8
3Ø.Opdal
14
1
4
16
B.Jákupsstovu
2
19 13
J.Odeck 2
2
1
1
88
S. Bråthen
Samfunnsfag
3
1
A-K Wallace
17
11
P. Sætre
2
77
NJ.Berland
17
2
H. Arntzen
A. Løkketangen
47
1
K. Danielsen
K.A. Olsen
5
6 16
1
8
4
D. Woodruff
1
7
26 5 5
25
10
1
J.MolkaB. Jæger D. Tipper
M.Spring
2
Danielsen
6
1
LM Hvattum
1
6
6
15
O. Bø
2
O.Ohren
T.Crainic
11 2
K.Bedringås
5
H. Gammelsæter
13 4
B. Foss
Økonomi
1
Helsefag
1 R.4Michaelsen
1
1
3
20
1
2
4
S.
Vatne
4
J. Berg G-U.Stavik
1
1
3
H.Sundal
1
2
H.Bakken
Connected Network Tree of researchers and co-author links
Conclusions
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Network of researchers at HSM is a Scale Free
network. (existance of hubs, clustering
coeffiencient)
Co-authors are not chosen randomly.
Co-authorship & Publication count: (cannot claim
causality)
– Average # of co-author per paper is the
same regardless of the total # of publications
per author. (does not help)
– Average # of unique associations is related
to a total # of publications per author. (helps)

Role of “connectors” (nodes with a high # of
external links) are important
– They often have high publication counts.
– They have more external contacts.
– They are more likely to hold a joint appointment
(again not causal).