The Role of Sociograms in Social Network Analysis

THE ROLE OF SOCIOGRAMS
IN SOCIAL NETWORK
ANALYSIS
Mar yann Durland Ph.D.
EERS Conference 201 2
Monday April 20, 10:30 -12:00
FORMAT OF PRESENTATION
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Part
Part
Part
Part
Part
I SNA overview – 10 minutes
II Sociograms Example 1 - 25 minutes
III History & Development – 10 minutes
IV Sociograms Example 2 – 25 minutes
V Questions &Answers – 20 minutes
PART I - WHAT IS SNA?
 Methodology for analyzing relational data Uses
matrix data for analysis (graph theory, matrix algebra)
 Uses sociograms or maps for visualization and data
(graph theory, visualization of data)
 Uses both simple & complex algorithms (matrix
algebra, graph theory)
 Is focused on the whole -structure, patterns, systems
(history)
 Looks at both the whole & parts within context of
whole (history)
 Has multiple applications aligned with theories
(support, structural holes, leadership, diffusion)
3
RELATIONAL DATA
 Relational data means that in some form or another
the data measures a connection between two points.
The two points might be cities and the connection
could be railroad lines, or one way streets, or stop
lights, or friendships, co-memberships, support, etc.
 SNA begins with the connection or absence of a
connection between two points
 Points might be towns, street corners, staff, a
classroom, members of a group, a team, an
organization, etc.
T YPES OF RELATIONSHIPS







People to people, but also:
Activities
Actions
Events
Materials & Resources
Ideas
etc.
5
RELATIONAL DATA COMES FROM
RELATIONSHIPS
coaching
Communities of practice
exchange
kinship
Diffusion of methods
power
groups
Teams
gossip
trust
mentoring
Matrix org Sharing info
communication
Working Relationships
innovation
Knowledge networks
Leadership
Communities of Practice
advice
conflict
friendship
influence
Club membership
Research
6
RELATIONSHIPS
 Defining Relationships
 Based on theory – support, leadership
 Based on behavior – defined by program or project
 Combination of both
 Measuring Relationships
 Align measure to behavior
 Use multiple measures
 Look at all levels (as results indicate, or aligned to theory)
 Network
 Sub-groups
 Individual
7
IMPORTANCE OF SOCIOGRAMS IN SNA
Foundation for SNA - History
Has features or characteristics that can
and cannot be measured (graph theory)
Adds context to measures (graph theory,
program theory, social science theory)
Locates the position within a network,
based on a measure, which is different
from a rank or score.
PART II READING SOCIOGRAMS
Nodes & lines
Direction/or not
Coded by attributes
or measurement
This is a
tree
This line is a
bridge
Person 2, 3,
and 1 form a
clique
Person 2 is a
cutpoint
•
•
•
•
•
Square Nodes
Non-directional lines
No attribute or measurement info
One network (person 1-5)
Person 2 has an Indegree of 3. Persons 3, and 1 have
an Indegree of 2. Who is in a better or more critical
position?
9
EXAMPLE 1: COLLABORATION AND
SPREAD OF TEAMS WITHIN NETWORK
Frequency of connections
 How are teams connected
 What is the structure of connections
(pairs, cliques, ego network, etc.)
 How is the overall structure organized?
(grade levels, peers, across grades)

10
SOCIOGRAMS
 Sociograms are created by software programs that
use algorithms to plot the nodes and ties or lines.
 Among other elements in the formulae, these
algorithms include four basic “rules” for creating a
sociogram;
 push unconnected nodes away from each other,
 pull connected nodes closer together,
 adjust for line length, so that lines are not too long or too
short, and
 position nodes and connections to minimize line crossings.
SCHOOL 1 – THE BIG PICTURE
Team members are
yellow
Highly connected
to each other, and
central to the
network (connected
to others as well)
Edges of
sociogram– nonrespondents, few
choices, etc.
12
RECIPROCAL VIEW – CODED BY AREAS
The bold lines
indicate mutual
connections.
Square nodes are
team members, within
their grade levels.
This map is by grade
levels (Primary,
elementary and
middle). Many
reciprocals are by
grade level, but not
all.
13
60-61 Pre-k, K
98 Other
99 AP
100 Principal
14
CLIQUE DATA
1:00 ORG1
ORG2
ORG5
ORG3
ORG4
2:00 ORG1
ORG2
ORG3
ORG4
ORG6
3:00 ORG1
ORG4
ORG6
ORG7
4:00 ORG1
ORG4
ORG8
5:00 ORG1
ORG11
ORG12
6:00 ORG1
ORG12
ORG13
7:00 ORG1
ORG14
ORG15
8:00 ORG1
ORG14
ORG16
ORG15
CLIQUE OVERLAP


Cliques are at
least three
people, and
almost all of
them talk to
each other.
School 1 has
94 cliques
from size 3 to
7 members
16
EGO NETWORKS FOR TEAM-
RECIPROCATED BY FORMAL GROUP
18
PART III. HISTORY
 Jacob Moreno developed the sociogram. In the beginning it
was a piece of paper, with people as the points, and their
connections to each other as lines. (1930’s)
 Additions to the field were from many fields including
anthropology, sociology, matrix algebra
 New fields developed such as graph theory
 During the middle 1980’s computer technology and speed
prompted interest
 2012, now at a heightened level of interest, from data
analysis to visualization
GRAPH THEORY
 The mathematical study of the properties of the formal
mathematical structures called graphs.
Simple Graphs
Trees
Gear Graphs
DIFFERENCES – NET WORK ANALYSIS VS.
STUDY
 Network Analysis
 Whole structure
 Structural features, Structural characteristics, Subsets of the whole
and/or Individuals within the whole
 Sociograms
 Data Analysis
 Some statistical analysis
 Network Studies
 A network measure is used as an attribute
 Generally only one measures, as an individual “score”, but not connected
to the whole
21
ATTRIBUTE DATA
Case
Gender
School age
Club1 Teacher
Suzy
F
GW
11
1
Scott
Casey
M
GW
11
1
Scott
1
JT
M
IP
10
1
Scott
1
Tommy
M
IP
9
Smith
1
Isabel
F
IP
10
1
Jones
Rose
F
GW
11
1
Jones
Spring
F
GW
9
Maple
Club2
Club3
Grade
Bus
A
47
C
47
1
B
47
1
A
47
A
47
D
47
A
47
1
1
MATRIX DATA
Outdegre
Read left to
right; 1st Row
is the chooser
and their
choices
Simplest Measures
1. Freeman’s
Indegree- who
choose me is the
column total.
2. Freeman’s
Outdegree – who I
chose is the row
total
Indegree
23
SEPARATED OUT BY AREA
24
EXAMPLE 2. HOW
 Defining relationships
 Based on theory – support, leadership
 Based on behavior – defined by program or project
 Combination of both
 Measuring relationships
 Align measure to behavior
 Use multiple measures
 Look at all levels (as results indicate, or aligned to theory)
 Network
 Sub-groups
 Individual
25
Sample from Internet
Component 1: Develop a network of strategically placed and financially viable community health centers in Clark
County for the uninsured/ underserved to access their primary health care needs.
Descriptions
Resources
Activities
Outputs
Outcomes
Impact
Appropriate physical
locations that
provide ready
access and are
free of barriers
Determine the best sites
through research
of target
populations and
through consensus
of CCHAC
members
Secure funding to
equip and staff
facilities
Maximize funding
through an
effective RFPbased selection of
providers who will
run the centers
Secure funding to build
an appropriate
MIS system
Maximize funding by
building, testing
and refining the
MIS system
among existing
centers, and by
hiring competent
MIS staff.
Target population will
obtain quality
primary health care
at the centers.
The perception that
quality health care
for the poor/
uninsured/
underserved is
available only in
hospital
emergency rooms
will be dispelled.
The health and wellbeing of members
of the target
population will
improve.
CCHAC’s
understanding of
the target
population will
improve.
CCHAC’s ability to
effectively meet
the primary health
care needs of the
target population
will improve.
Will eliminate the
use of
emergency
room visits
for primary
care services
in Southern
Nevada.
The overall health
and well
being of
Southern
Nevadans in
general will
improve.
CCHAC’s
mission will
evolve to
include the
entire range
of
healthcarerelated and
social
services.
CCHAC MIS committee
Selected providers will
Appropriately
equipped and
staffed facilities
MIS that allows
effective
oversight, data
gathering,
tracking,
reporting, and
appropriate
sharing of
patient
information
among clinics
Assumptions
CCHAC continues
Target population will
utilize referrals from
the centers to
medical specialists
and other needed
health care and to
needed social
services.
Client use of the centers
and their satisfaction
will be effectively
tracked, recorded,
reported on, and, as
appropriate, shared
among centers.
26
Quality primary health
Once it ends,
EXAMPLE FROM A LOGIC MODEL
 Target population will utilize referrals from the centers to
medical specialists and other needed health care and to needed
social services.
 Use referrals is an anticipated behavior that will occur as a result
of this project. This implies a connection, or a relationship
Center
Medical
Specialist
Client
This connection is the
behavior
27
QUESTIONS TO ASK: GO BEYOND THE
ASSUMPTIONS OF THE STATED
 What program components indicate a relationship? ( target
population use referrals from health center s, to specialists, other
ser vices ?)
 Can you define the relationship(s )? ( From direct relationship with
health center s to new relationships; also the center s to the specialists )
 Who are the actors, groups, etc in the relationship(s )? ( target
population, health center s, specialists, other.)
 What behaviors, actions, and activities would you expect in this
relationship and by whom? ( Target population initiates new
relationships, what is role of center s?
 How does the relationship(s) contribute to the success of the
project or to understanding the project
28
INFORMAL NETWORKS
 Defined by theory of relationships & questions






Mentoring relationship
Work with
Do research and write with
Consider important to career
Respect and would ask for work related help from
Would like to work on a committee with
29
FREEMAN’S INDEGREE
N umber of times a person is chosen by others / n -1
(column total/n-1)
30
DEGREE CENTRALIT Y
31
NODES BY INDEGREE
FREEMAN’S BETWEENNESS
How much an individual is indirectly linked
to others, and to what extent an individual
is between two others
C b(i) = SSb ijm , across all n 's.
b ijm = g ijm/ jm;
g ijm is equal to the number of geodesics
containing i that are linked to both j and m;
jm is equal to the number of geodesics
linking j to m.
33
COMPLETE SOCIAL NETWORK
Top 3 Choices
Old Group and
New Group
are NOT integrated
34
PC2 - DECLINING
Principal
36
PC1 - IMPROVING
Principal
37
CLIQUE OVERLAP
COMPONENTS
WHAT TO MEASURE?