Social Network Analysis: A Non-Technical Introduction

José Luis Molina Universitat Autònoma de Barcelona

joseluis.molina@uab.es

Social Networks?

• Social networks as a metaphor of a complex world.

• Social networks as social networking platforms.• Social networks as a way of empowerment of

local actors for improving the current situation.• Social networks as a Theory and Methods for

studying social and cultural phenomena.

Network Science …

• An approach to the study of complexity …• Massive data about telecommunications,

internet, biology, languages, political networks …

A long history ...

Moreno Sociometry (1934)

Graph Theory (e.g. Harary 1963)

Manchester School (1954-1972)

American Sociology (1976)

INSNA & Computers & Interdisciplinariety

Who is working in SNA today ...?

• The International Network for Social Network Analysis (INSNA)

Network data ...

For making visible relations among entities we have several options:

Direct observation. Database of interactions. Asking (people):

Name generators.

Sociograms ...

... and Matrices ... 1 1 1 1 1 1 2 3 4 5 6 7 8 9 0 1 2 3 4 AMRVGBEGJSJMMOCRPPGGJLMAFGDE - - - - - - - - - - - - - - 1 AMG 0 0 0 0 0 0 1 1 0 0 1 0 0 0 2 RVT 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 GBB 0 0 0 0 0 1 0 0 0 1 1 0 0 0 4 EG 0 0 0 0 0 0 0 0 0 0 1 0 0 0 5 JSP 0 0 0 0 0 0 1 1 0 0 1 0 0 0 6 JMF 0 0 1 0 0 0 1 0 0 1 1 0 0 0 7 MOS 1 0 0 0 1 1 0 1 0 0 1 0 0 0 8 CR 1 0 0 0 1 0 1 0 0 0 1 0 0 0 9 PP 0 0 0 0 0 0 0 0 0 0 1 1 0 0 10 GG 0 0 1 0 0 1 0 0 0 0 1 0 0 0 11 JLM 1 1 1 1 1 1 1 1 1 1 0 0 0 0 12 MAR 0 0 0 0 0 0 0 0 1 0 0 0 1 0 13 FG 0 0 0 0 0 0 0 0 0 0 0 1 0 0 14 DES 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Sociocentric and egocentric networks …

• A sociocentric network is the outcome of a tie definition upon a list of nodes.– Normally a Tie Definition refers to

an Institutional Setting (kin, workmates, friends, neighbours, cooperation with, report to …).

• An egonetwork is the subset of ties surrounding a given ego within the sociocentric network.

• So, sociocentric and egocentric networks refer to a single Institutional Setting.

Alter

Alter

Alter

EgoAlter

Personal Networks

• A Personal Network is the outcome of using one or more Name Generator about Ego’ alters AND a Tie Definition for connecting her alters.

• If the list of alters is long enough (30 or more on average) all institutional settings in which ego participate will be represented (kin, friends, coworkers …)

Fundamentals …

• Vargas-Quesada, Benjamín, Moya-Anegón, Félix de (2007). Visualizing the Structure of Science. [pdf]

• Actor. In a social network graph, the actor may also be referred to as the node, vertex, or point. The actor does not necessarily have to represent a concrete unit or individual; it may also be a company, institution, or social group.

• Link. This may also be called a connection or line, and it may be directional (arc) or non-directional (edge), depending on whether it indicates the orientation – from one actor to another – or does not. Links may or may not be weighted.

• Adjacent Actors. Actors that can be found in direct relation or connection via a link.

• Neighborhood. Set of actors with which a given actor or node is adjacent.

• Path. This is the sequence of links and actors that connect two non-adjacent actors, without repeating any of them.

• Geodesic Distance. It is the shortest path between two nodes or actors of the network.

• Diameter. It is on average the shortest path between every two nodes or actors in a network.

• Isolated Actors. Actors that have no link or relation with any other actor in the network. They may also be called disconnected actors.

• Components. This name is given to each one of the subgraphs or subgroups that make up a network.

• Bridge. It is the link that if it is eliminated, the graph becomes disconnected.

• Cutoff Point. A node or actor is considered to be the cutoff if, by eliminating it, the graph is left disconnected.

Current Applications ...

Scientits networks, scienciometry … Organizations Internet Social Support Discourse Analysis Data-mining ...

A “Perfect” Network ...

• “Edges” = undirected lines.

• Degree: A = 4 B, C, D, y E = 1

A

B

CD

E

Degree ...

• “Arcs”= directed lines. • Indegree of A=0 B,C,D,E = 1.• Conversely, the

outdegree is: A= 4 B, C, D y E = 0

A

B

CD

E

Matrix

A B C D E

A 1 1 1 1

B 1 0 0 0

C 1 0 0 0

D 1 0 0 0

E 1 0 0 0

Betweeness ...

The betweeness counts the times that a node occurs in the geodesics of the network (that is, in the shorter paths between each pair of nodes).

A

B

CD

E

A=12 A = 0

A

B

CD

E

Betweeness ...

A= 0 (there is not a path that occurs through it), as D and C.

B= 1E= 1

A

B

CD

E

Closeness ...

Closeness measures the capacity of

a node to reach the rest of the nodes of the network. For computing this measure is necessary to summarize all the geodesics of each node with the rest of nodes of the network. This measure is the farness. If we compute the reciprocal we can obtain the closeness.

Closeness ... (ii)

For doing this calculations is necesary to

convert first the oriented data in reciprocal data:Farness of A = 6 (AB:1; AC:2;A E:1;AD:2)Farness of B = 7 (BA:1; BC:1;B E:2;BD:3)Farness of C = 10 (CB:1; CA:2;C E:3;CD:4)Farness of E= 7Farness of D= 10All geodesics = 40The closeness of A= 40/6= 6,667 or 66,67%.B= 40/7= 5,714 = 57,14%C= 40/10 = 4 = 40%

A

B

CD

E

Centrality ...

Clustering ...

Present & Future ...

Evolution of Networks

Community Studies

…

... It is up to us