1. TODAY
• Lecture 1 part 1 (40 mins).
What is social network analysis? Brief history
• Tutorial 1 (30 mins)
Organization of groups and selection of topics
• Lecture 1 part 2 (40 mins)
Data collection
• Workshop 1 (30 mins)
• Facebook demonstration (10 mins)

2. LECTURE 1: PART 1
Why study networks?
Many phenomena seem to be structured as networks:
- Neural networks
- Circulatory systems
- Organizations
- Economies
- Ecologies
- …
An actor’s position in a network shapes opportunities and constrains, and may be able to
predict outcomes of her behaviour.
What happens to people an actor is connected to may influence her own behaviour as well
Eg: I want to sell my product in china, I need a Chinese contact who introduces me to the
market.
Eg: I want to get involved in a student political movement to support gay marriage, but my
parents are strongly against it
Eg: all my friends have bought an iphone, it is more likely that I
will buy one as well

3. Relationships among entities.
- Social and inanimate
- Individual and collective
What are networks?
Egonetworks
Whole networks
DEPENDENCIES
Actors and attributes
• Categorical (male/female)
• Continuous (56 year old)
• Ordinal (low class/middle class/upper class)
Relationships
• Multiple (being married, being coworkers, living together)
• Valued (continuous, having known each
other for 56 years, or ordered, like
exchanging emails once a week, every
month)
• Directed
• Indirect connections (chains and paths)

4. What are relations?
What are the differences between relational status and events?
Each tie gives a corresponding network. Multiple ties produce multiple networks (friendship,
advises, etc.)
 Relational states: continuous and persistent relationships
 Relational events: discrete events
States:
• Similarities: antecedents and consequences of social ties, occasions
• Roles: permanent relations
• Cognition: thought and feelings people have of each other, not directly observable, but
inferred from interaction or directly asked to people
Events:
• Interaction: observable behaviours between two people
• Flow: outcomes of interactions, tangible (money) and intangible(information, beliefs)
Similarities
Location
Same
spatial and
temporal
space
Participation
Same clubs,
same events
Relational
states
Relational roles
Other
Attribute
Kinship
Role
Same
gender,
same
attitude
Mother
of, sibling
of
Friend of,
boss of,
student
of,
competit
or
Relational events
Relational cognition
Percep-t
Affective
ual
Likes,
hates
Knows,
knows of,
sees as
happy
Interactions
Sold to,
talked
to,
helped,
fought
with
Flows
Informati
on,
beliefs,
money

5. What is the goal of network analysis?
Network variables as independent/explanatory: network processes are used to explain and
predict outcomes.
- Brokers may have advantages
- Closure my be restraining
- Centrality may produce stress
Network variables as dependent/outcomes:
- Homophily may explain relationship formation
Network variables as independent/explanatory
Network variables as dependent/outcomes
Friendship between pairs of farmers to predict
Dyad level which pairs of farmers make the same decision
about going organic
Similarity of interests (e.g., sky diving) to
predict who becomes friends with each other
Centrality in organizational trust network to
Node level predict who is chosen for promotion
Extraversion to predict who becomes central
in friendship network
Shortness of paths in a group’s communication
Network level network to predict group’s ability to solve
problems
Type of organizational culture (emphasizing
either cooperation or competition) to predict
structure of the trust network

6. Brief history of SNA
See:
Freeman L. C., 2004, The development of social network analysis, Empirical Press,
Vancouver.
Prell C., 2012, Social Network Analysis. History, theory and methodology, Sage, London.
Chapter 2: 19-52.
SNA emerged out from
- Psychology
- Social anthropology
- Sociology
But since the origin it was interdisciplinary: Elizabeth Both first anthropologist, then
psychologist; Mayo (psychology) and Warner (social anthropology)

7. Psychology
• Jacob Moreno
Student of psychiatry in Vienna, then moved to US in 1925 and developed sociometry (30s)
How social relations affect psychological well being. Sociograms are visual depictions of
individuals and their relationships. Sociometry faded in the 50s: frustration for the
difficulties in uncovering meaningful patters when networks reach a certain size.
In the 40s, mathematicians started using matrices and graph theory to meet this demand.
• Kurtin Lewin
He similarly studied Gestalt theory (vs behaviourists) and moved to US in 1930s. In 1945 he
became the director of the Research Centre for Group Dynamics, MIT.
Field theory: the totality of coexisting facts which are conceived of as mutually
interdependent.

8. Psychology
• Alex Bavelas
Student of Lewin, and director of the Group Networks Laboratory (at MIT, from Lewin
centre). They began studying the effects of different communication network structures on
the speed and accuracy with which a group could solve problems.
Development of the concept of centrality: central
actors are optimally positioned for integrating
Information from dislocated parts of the network.
Centralization as a global measure
• Luce and Perry, and the concept of clique

9. Psychology
• Festinger, Cartwright and Harary
Second centre to spring out of MIT, at University of Michigan (50s). Collaboration with UK
(1947). Through the journal Human relations influence over E. Bott
• Balance theory from Heider:
they re-defined it in structural terms using graph
theory, extending it from individual cognitive states
to any social phenomena that could be represented
in network terms.
•
-
Current psychological work:
Social influence
Homophily
Social exchange theory

10. Social Anthropology
• Radcliffe Brown
UK, Australia, Chicago, Oxford with Gluckman, etc.
Structuralist, but with more emphasis on social relations that structural functionalism.
Networks can help to move beyond abstract concepts (reifications) of culture and class.
• Lloyd Warner
Student of Radcliffe Brown who moved to Harvard and worked with Mayo to the research
at the Western Electric Company and at the Hawthorne factory.
Yankee city study, anthropological study of a urban setting.
In Chicago Deep South, on the impact of race differences on social stratification (2 mode
Davis data).

11. Social Anthropology
• Max Gluckman
First chair of Manchester’s dept. of social anthropology and sociology
50s and 60s: Manchester school.
Study of social networks in natural settings, cross cutting ties in the development of
conflicts.
• James Clyde Mitchell
British sociologist who followed Gluckman in Manchester in 1965 as Chair in Urban Studies.
Clyde was interested in the study of social structure through the observation of regular
patterns of social relations that persist over time. Social networks as an opportunity to mix
the qualitative and thick descriptions of the cultural peculiarities of structural environments
with a “non-quantitative mathematical way of rigorously stating the implications entailed in
a set of relationships” (Mitchell 1969: 1).

12. Social Anthropology
London School of Economics
• Elizabeth Bott
Many contacts with the Manchester school.
Married couples and personal networks.
Density
• John Barnes
Bott’s colleague, and the first one to use the term social networks in a fiend study
• Siegfrid Nadel
Role analysis
MIXED METHODS APPROACH

13. Sociology
• Simmel:
- dyads and triads
- differentiation of social circles
Peculiarities of urban societies in relation not only to the increase in the population size, but
in the consequential differentiation of social circles where the structure of social relations is
organised in multiple, sparse and partially overlapping clusters.
• References to the fundamental role of interconnections as irreducible elements of social
life can be found across a vast range of thinkers like Marx, Tönnies, Spencer, Weber,
Durkheim.
• Pareto: elites are constantly reproduced by individuals and their investment in
relationships
• Harvard: interest in Pareto, Warner, Parsons, Merton, Mayo. Mayo supervises Homans.
Homans develops a theory of social relations and social groups. Small group research (50s)

14. Sociology
At the same time of Homans, Merton was at Harvard, who lately trained Coleman, Blau,
Kadushin.
• Coleman
Diffusion and social capital
• Kadushin
Simmel’s social circles
• Blau moved to Columbia, and trained Davis
Clustering
Transitivity
Triad census (Holland and Leinhardt)

15. Sociology
At Harvard in the 70s
Harrison White
Maths, physics and sociology.
Chains of opportunity applies algebraic models to the study of the job market.
Whole networks VS egonets (Manchester school)
Block modelling and positional analysis
Among his students:
Granovetter
Bonacich (centrality measures)
Wellman

16. The Mitchell Centre
• Established in 2009
• Nick Crossley, Martin Everett, Gemma Edwards, Elisa Bellotti, Susan
O’Shea, Kathryn Oliver, Mark Tranmer (CCSR), Johan Koskinen
(CCSR)
• Interests in social movements, covert networks, music networks,
scientific networks, personal networks, health networks, interorganizational networks…
• Mixed methods, development of methods for one mode and two
mode networks, multilevel analysis, network modelling, and
network dynamics

17. http://www.ccsr.ac.uk/mitchell/
MAILING LIST
SEMINAR SERIES EVERY WEDNESDAY 4pm. CHECK FB, BLACKBOARD OR THE WEBSITE FOR
DETAILS. SOCIAL TRIP TO THE PUB (AND DINNER) AFTERWARDS. EVERYBODY IS WELCOME!

18. TUTORIAL

19. LECTURE 1: PART 2
Data collection
Marsden P. V., 1990, Network data and measurement, Annual Review of Sociology, 16: 435463.
Social structures as patterns of specifiable relations of social units. Social structures place
opportunities and constrains on individual action according to one’s position.
Opportunities: social resources, social capital, social support.
Distinction between:
1. Existing social relations: important for diffusion mechanisms/Perceived networks
(cognitive): importance for social influence on attitudes and opinions
2. Momentary reactions/Routinised and recurrent relationships

20. Boundaries specifications
Focus on interdependencies, therefore the omission of nodes (and relationships) would
alter the overall structure
Realist approach: subjective perception of actors who belong to the network
Nominalist approach: observer standpoint
Egonets:
• star, first zone, second zone
• Unlimited VS limited number of alters
• Type of ties
• Alter’s roles and attributes
• Normal sampling
Whole networks
• Membership criteria (roster method)
• Snowball
• Participation (eg: events)

21. How to collect data
• Name generator (egonet and whole net). Ego attributes, ego-alter
ties, alter attributes, alter-alter ties
• Position generator (egonet). Ego attributes, frequency of egoalter ties (with no names), alter ties attributes
• Resource generator (egonet), Ego attributes, frequency of egoalter ties (with no names), alter ties attributes
Data collected via
• Surveys
• Qualitative interviews
• Ethnographic observations
• Archival data

22. Name generator
Can be used for egonetworks as well as whole networks.
Question
Answer
Data
-Who did you discuss matters
important to you in the last 3
months?
John
Jack
Bob
Ego
John
Jack
Bob
-Who did you ask for advice in the
past 3 months?
John 2 times
Jack 3 times
Bob 1 time
Ego
John
Jack
Bob
-Who has lent you money?
Bob 15000£
Jack 10000£
Ego
John
Jack
Bob
-Who would you discuss matters
important to you with?
-Who did you lend money to?
John 25000£

23. Who did you lend money to?
Who did you borrow money from?
How much?
How much?
25000
0
Bob
0
15000
Jack
0
10000
John
….
Alters’ atttributes
Who did lend money to who, of
which you are aware?
John
Bob
Jack
0
5000
3000
Bob
2500
0
0
Jack
0
7000
0
John
Gender
Age
No. Of kids
John
1
50
3
Bob
1
46
0
Jack
1
72
2

24. Adjacency Matrices
Binary
Jim
Jim Jill 1
Jen 0
Joe 1
Jill Jen Joe
1 0
1
- 1
0
1
1
0 1
-
Jill
Jen
1
3
Jim
9
Valued
Jim
Jim Jill 3
Jen 9
Joe 2
Jill Jen Joe
3 9
2
- 1 15
1
3
15 3
-
3
15
2
Joe

25. Directed vs undirected ties
• Undirected relations
– Attended meeting with
– Communicates daily with
• Directed relations
– Lent money to
• Logically vs empirically directed ties
– Empirically, even undirected relations can
be non-symmetric due to
measurement error
Bonnie
Bob
Biff
Betty
Betsy

26. Position generator
Do you know anyone
who is a/an
U&S2
ISEI3
acq.
% yes
family
member
friend
lawyer
86
83
47
40
25
35
doctor
84
87
50
41
19
40
policymaker
82
70
45
33
28
39
engineer
76
68
65
24
21
56
informationtechnologist
68
70
66
30
27
42
manager
67
69
66
21
27
52
directorcompany
67
69
71
24
24
52
tradeunionmanager
66
65
17
57
20
23
scientist
65
71
42
26
28
46
highercivilservant
64
61
53
35
21
44
Source: Position Generator measures and their relationship
to other Social Capital measures
Martin Van der Gaag, Tom A.B. Snijders, Henk D. Flap
http://www.xs4all.nl/~gaag/work/PG_comparison.pdf

27. Resources generator
Source: Position Generator measures and their
relationship to other Social Capital measures
Martin Van der Gaag, Tom A.B. Snijders, Henk D. Flap
http://www.xs4all.nl/~gaag/work/PG_comparison.pdf

28. Roster method (whole networks)
Everyone belonging to the network has to fill in the questionnaire
Here there is the list of people who
work in your office
WIthin them, who do you
ask for advice?
Bill
2
Joe
0
Anna
0
Carol
1

29. Surveys
Realist approach: they elicit ego’s subjective perception of actors who belong to his/her
network.
They can focus on
• the content of exchange between people, by asking whom ego discuss important
matters with, or socialise (exchange approach)
• the role of the relationship, by asking to list friends, neighbours, co-workers, and the
like (role-relational approach)
• the strength of the relation, but asking whom ego feels especially close to (affective
approach)
• the frequency of communication, by asking whom ego is in contact with (how often,
via which media) over a certain period of time (interactional approach)
• the locality of ties, by asking who lives nearby or in the same geographical area
(geographical approach).

30. Surveys
• Laumann (1973): in 1965 surveyed 1013 native-born, white men, between the ages of
21 and 64, in the greater metropolitan area of Detroit, asking them about three closest
network members.
• Wellman (1993): designed the sociological component of a series of East York studies.
Large study administered in 1967 and 1968. Survey of 845 respondents, to whom he
asked the names of all the people living in their household, and the initials of the
people outside the household that they feel closest to. The name generator asked only
the about the first six people, but also added the information on how many they feel
close to on top of these 6 (if any), which gives an approximation of the size of the
network. Together with the list of names, Wellman also used name and ties
interpreted, asking a wide range of alters’ attributes (role, sex, occupation, where they
live) and the frequency, mean, and reason for contacts (how often they are seen, how
often they are contacted by phone or letter, who they get together with informally,
who provides help for everyday matters or in case of emergencies). Finally, alter-alter
ties are collected.

31. Surveys
• Fischer (1982a), in his study of personal networks in 50 urban and rural Northern
California communities, surveyed 1050 adults about their exchange of support
(emotional companionship, material). He uses 10 different name generators and 19
name and tie interpreters. 8 of those interpreters are asked for all the names elicited,
while 11 (gaining details about how long they have been known by ego, the frequency
of contact, how they were met) are asked only for the first five alters named. For each
pair of names he also asks if they know each other well, obtaining alter-alter ties.
• Burt (1984)Items for the US General Survey Election. Only one name generator is used
that elicits names of people ego discussed personal matters during the previous six
months. While no size boundaries are adopted, name interpreters are asked only for
the first 5 people named, for whom a 3 grades strength of alter alter-ties is also
administered. The strength of ego-alter ties is operationalized as especially close VS
moderately close, frequency of contacts, years of acquaintance, relationship content
(discussion topics), and role (kin, friend, etc.).

32. Visually aided data collection
Visualization is very common in social network analysis, but it is more often used in the
analysis rather than in the collection of data
• Fizgerald (1978) used a creative process for collecting relational information in Africa,
where she asked her respondents to write names of alters on plastic chips and to
arrange them according to the strength of the tie.
• Commonly used is the target, which consist in a series of concentric circles where ego
stands in the middle, and has to place the names of alters alongside the circles,
following the guideline that the nearer to the centre the closest the relationship. This
tool has been originally designed by Kahn and Antonucci (1980) and recently adopted,
for example, by Spencer and Pahl (2006) in their study of friendship. No alter-alter ties

33. Qualitative interviews
Realist approach
Qualitative interviews in network research are not used differently from any other
qualitative study, insomuch as they can take the form of semi-structured interviews, indepth interviews, thematic interviews, or life histories. However, when adopted in the
investigation of networks they normally aim at exploring the content of relationships, and
the meaning of the overall structure of individual social environments.
Mostly used in egonets, rarely in whole nets
By recording the subjective accounts of network structures, they aim to gain an insider
view of the interactional processes which generate those structures (Edwards 2010).
Already in East York study

34. Qualitative interviews
• Bidart and Lavenu (2005) interviewed 66 young people living originally in Normandy
(France), who were questioned every three years about the evolution of their personal
networks and the events marking their entry into adult life.
• Hollstein (forthcoming) combines fuzzy set analysis of qualitative material and network
data to investigate youth transition from school to work.
• Bellotti (2008a; 2008b) interviewed 23 single young adults living in Milan (Italy) about
the composition, dynamics and outcomes of their friendship networks.
• Bernardi et al. (2007) interviewed 64 young adults living in two cities in Germany in
order to investigate the social mechanisms at work or the variation in the composition
of the networks of informal relationships in relation to fertility behaviour.

35. Ethnographic observations
More common for whole nets
• Department of Social Anthropology and Sociology at the University of Manchester
mostly focussed on the use of observations for the mapping of interactions in various
settings.
• Epstein for the study of the spread of gossip (Epstein 1969a and 1969b)
• Kapferer used observations to map interactions between a group of African mine
employees who were engaged in surface work in the Cell Room of the Electro-Zinc
Plant of the mine (Kapferer 1969: 184).
• Wheeldon (1969) studied a coloured community in Southern Africa, focussing the
attention on six leaders who were frequently named by other members of the
community
• Boswell (1969) observed the mobilization of personal networks during periods of crisis
in the African city of Lusaka
Clyde Mitchell, 1969, (ed.), Social Networks in urban
situations, Manchester University Press, Manchester.

36. Ethnographic observations
• Studies mapped concrete interactions in a group of deaf teletype users, between
amateur radio operators, in a small social science research firm, and participants of a
university graduate program (Bernard and Killworth 1977)
• Observation of interactions between drug users (Curtis et al. 1995)
• Relationships between students, teachers, and parents in school classrooms (Haussling
2010)
• Conversational interactions and speaking turns in meetings of managers (Gibson 2005)
• Ethnographic studies of hidden populations (Schensul et al. 1999)
• Classic study of an Italian slum in Chicago (Whyte 1943), shadowing an egonet
• Similar to observations are diaries

37. Archival data
Whole net and egonet
information is not created for the purpose of the research, but pre-exist the data
collection process: this means that the researcher has a minimal influence in the
production of the data, especially compared to other form of direct inquiry like surveys
and interviews.
Nominalist approach: data selected independently from actors’ perceptions, and
according to the researcher’s goals
• Interlocking directorates
• Padgett and Ansell (1993): structure of relationships between oligarchic families in
Florence during Renaissance.
• Crossley on the development of the punk scene in London (Crossley 2008b) and
Manchester (Crossley 2009)
• Analysis of the structural advantages in obtaining funding in academic disciplines
(Bellotti 2012; forthcoming).
• Edward and Crossley on the egonetwork of the suffragette Helen Kirkpatrick Watts
(Edward and Crossley 2009).

38. RECAP
• SNA as a way to formalise relational structures and dependencies between actors. Nodes
and ties to visualise networks.
• Various types of nodes, and various types of relations
• SNA interdisciplinary. Psychology, social anthropology and sociology paths, all combined
with mathematics.
• Egonet ad whole nets
• Boundaries specifications in both approaches
• Nominalist VS realist approach
• Name generator
• Position generator
• Resource generator
•
•
•
•
Survey
Interviews
Observations
Archival data

39. References
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Bellotti E., Qualitative networks. Mixing methods in social research, Routledge, London, forthcoming.
Bellotti, E., 2008a. What are friends for? Elective communities of single people, in Social Networks, 30, 318-329.
Bellotti, E., 2008b. Amicizie. Le reti social dei giovani single, Milano, F. Angeli.
Bernard R. H. and P. D. Killworth. 1977 Informant Accuracy in Social Network Data II. Human Communications Research
4:3–18.
Bernard, H. R., E. C. Johnsen, P. D. Killworth, C. McCarty, G. A. Shelley, and S. Robinson. 1990. Comparing four different
methods for measuring personal social networks. Social Networks 12 (3): 179–215.
Bernardi L., Keim S., von der Lippe H., 2007, Social Influences on Fertility: A Comparative Mixed Methods Study in
Eastern and Western Germany, Journal of Mixed Methods Research, 1, 1, 23 – 47.
Bidart C. e Lavenu D. (2005), «Evolution of personal networks and life events» in Social Networks, 27, pp. 359 – 376.
Borgatti S.P., Mehra A., Brass D.J., Labianca G., 2009, Network Analysis in the Social Sciences, Science, 13, 323, 5916:
892-895.
Brandes U., Robins G., McCranie A., Wasserman S., 2013, What is network science?, Network Science, 1, 1: 1-15.
Burt R., 1984, Network items and the general social survey, Social Networks, 6, 293 – 339.
Crossley, N. (2009) ‘The Man Whose Web Expanded: Network Dynamics in Manchester’s Post-Punk Music Scene 19761980’, Poetics 37(1), 24-49.
Crossley, N. 2008b “Pretty Connected: the Social Network of the Early UK Punk Movement.” Theory, Culture and
Society 25, 6: 89-116.
Curtis R, Friedman S, Neaigus A, Jose B, Goldstein M, Ildefonso G. Street level markets: network structure and HIV risk.
Social Networks. 1995;17:229–249.
Edwards, G. and Crossley, N. (2009) ‘Measures and Meanings: Exploring the Ego-Net of Helen Kirkpatrick Watts,
Militant Suffragette’, Methodological Innovations On-Line 4: 7-61.
Edwards, G., 2010. Mixed-Method Approaches to Social Network Analysis. Review paper, ESRC National Centre for
Research Methods.
Fischer, C.S., 1982a. To Dwell Among Friends. Personal Networks in Town and City. The University of Chicago Press,
Chicago and London.

40. References
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Fitzgerald, M. 1978. The content and structure of friendship: An analysis of the friendships of urban Cameroonians.
Unpublished doctoral dissertation, Department of Anthropology, University of Toronto.
Freeman L. C., 2004, The development of social network analysis, Empirical Press, Vancouver.
Gibson D., 2005, Taking Turns and Talking Ties: Networks and Conversational Interaction, AJS 110 6: 1561–97
Häussling R., 2010, Allocation to Social Positions in Class : Interactions and Relationships in First Grade School Classes
and Their Consequences, Current Sociology 58, 1: 119 – 138.
Hollstein B., Fuzzy Set Analysis of Network Data as Mixed Method. Personal Networks and the Transition from School
to Work. In: Hollstein B. and Dominguez S. (Eds.): Mixed-Methods Social Network Research. New York: Cambridge
University Press, forthcoming.
Kahn, R. L., & Antonucci, T. C. (1980). Convoys over the life course. Attachment, roles, and social support. In P. B. Baltes
& O. G. Brim (Eds.), Life-span development and behavior (pp. 254–283). New York: Academic Press.
Laumann, E. O., 1973, Bond of Pluralism: The Forms and Substance of Urban Social Networks, Wiley, New York.
Lin N., and Dumin M., 1986, Access to occupations through social ties, Social Networks, 8, 365 – 385.
Marsden P. V., 1990, Network data and measurement, Annual Review of Sociology, 16: 435-463.
Mitchell, Clyde , 1969, (ed.), Social Networks in urban situations, Manchester University Press, Manchester.
Padgett John F., Ansell Christopher K., 1993, Robust Action and the Rise of the Medici, 1400-1434, The American
Journal of Sociology, Vol. 98, No. 6., pp. 1259-1319.
Prell C., 2012, Social Network Analysis. History, theory and methodology, Sage, London. Chapter 2: 19-52.
Schensul J. J., LeCompte M. D., Trotter II R. T., Cromley E. K., Singer M., 1999, Mapping social networks spatial data,
and hidden populations, Altamira Press, Plymouth.
Spencer, L., and R. Pahl. 2006. Rethinking friendship. Princeton, NJ: Princeton University
Van der Gaag Martin , Tom A.B. Snijders, Henk D. Flap, Position Generator measures and their relationship to other
Social Capital measures , http://www.xs4all.nl/~gaag/work/PG_comparison.pdf
Wellman B., 1993, An egocentric network tale: comment on Bien et al. (1991), Social Networks, 15, 423 – 436.
Whyte W. F., 1943, Street Corner Society. The social structure of an Italian slum. The University of Chicago press,
Chocago and London.

41. WORKSHOP 1

42. FACEBOOK
Course’s page
Egonet (for handout)