Keystone sector methodology:network analysis comparative study



REAL


Keystone sector methodology applied to Portugal

LOCAL CENTRALITY            LOCAL PRESTIGE

Mean = 15.6                                 Mean = 15.6

___________Sector_______________

Value________

___________Sector_____________________

Value_________

Local Authority

38

Student Univ. Assoc.

82

University

32

YMCA

82

Local Firemen

23

Private Transport firm

82

Association Text. Ind.

22

Employment Pub. Inst.

82

Pub. Inst. SME

21

Public Health Care C.

82

Student Univ. Assoc.

20

National Transit Police

82

Association Retailers

20

Hospital

82

Employment Pub. Inst.

19

Church

82

Public Health Care C.

19

Political party

82

Training Inst. Textile

19

Political party

81

High School

19

Local Radio

72

Pub. Inst. Foreign Com.

19

Private Insurance Comp.

55

Local Newspaper_______________

19____________

High School__________________________

___________50

Overall, Public sector and non-profit institutions are much more represented
than private firms all over the three matrices, enhancing the shift we predicted in our
previous design.

4.2.2 Centrality

After looking at each player local centrality and prestige, we checked for
Global Centrality in the network.

Global centrality is measured by the length and number of carrier and multiple
step-path simultaneously; this indicator captures the position of strategic significance
within the network or the best positioned entities to profit from the structural holes and
increase the whole social network efficiency. Of course, this strategic significance
depends on intermediaries, but global central actors can have important widespread
effects.

To test for these location opportunities, we used three important concepts in
social network analysis: closeness, betweeness and efficiency.

Closeness or distance that is a measure focusing on how close an actor is to all
the other actors in the total network (Wasserman and Faust, 1997). The main idea is
that actor
ai is considered central if it can easily interact with all the others, in the
shortest path through other well connected actors. In the economic sense it is the one
who can efficiently improve the flows in the net, benefiting the whole connection,
reaching clusters of other actors already connected among them.

Betweeness is another measure that one can compute, counting the number of
geodesics linking actors
j and k (all the geodesics will have the same length) and then
determine how many of these geodesics contain actor
i, for all distinct indices j, k and i.
So, the index for
ai will be the sum of the estimated probabilities over all the pairs of

16



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