social network analysis: concepts, applications, analysis of social structures using secondary data
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Social Network Analysis: Concepts, Applications, Analysis of Social
Structures Using Secondary Data
Liaquat HossainSciences of Learning Winter Institute Workshop
The University of Hong KongHong Kong, 14 January 2014
Email: lhossain@hku.hk
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Agenda• Introduction to Social Networks• Visualising & Interpreting Social Networks• Social Network Data Collection & Analysis• Social Networks Correlates to Coordination
– Enron Email Communication Corpus– Visualisation of Enron Communication Network
• Research Framework• Methods • Results
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Introduction to Social Networks
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Social Network Analysis• Social Network – A set of actors and relations that hold the
actors together
• SNA – “The disciplined inquiry into the patterning of relations among social actors, as well as the patterning of relationships among actors at different levels of analysis (such as persons and groups)” (Breiger, 2004)
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Growth of Social Networks• Social Networks research has been growing exponentially
over the past decades
Source: Otte & Rousseau (2002)
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Distribution of Social Network Research
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1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 20002002 2004
Year
Num
ber o
f Pap
ers
Publ
ishe
d
Internet
Social Capital
Terrorism
Urban &CommunityFamily, Kinship& FriendshipOrganisations
Delinquincy
Diffusion
Social Support
Infection &DiseasesHealth
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At the Beginning of the Hype Curve
Source: IBM (2005)
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Concepts: Relations and Ties• Relations – connects actors (eg. Friendship, colleagues,
kinship)• Tie - a relation that is established between two or more
entities from the moment information or resources are exchanged
• Multiplex Tie – Connections based on many relations• Ties are characterised by content, direction and strength
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Visualising & Interpreting Social Networks
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Collaboration Network
Source: Otte & Rousseau (2002)
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Academic Collaboration Ties (1990-1994)
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Academic Collaboration Ties (1995-1999)
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Academic Collaboration Ties (2000-2004)
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Sexual relations Colorado Spring dataBy Gender (Morris, Moody et al.)
MaleFemale
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Social Network Data Collection & Analysis
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Whole or Sociocentric Approach• Focus is on measuring structural patterns of interactions
and how the patterns explain outcomes (eg. concentration of power or resources within groups)
• Actors are usually known or determined ie. network boundaries are a priori defined
• A roster of names is usually needed to formulate the adjancency matrix
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An Adjacency MatrixSeeks advice
from John Ken Smith Jacky Carl Winnie Will Daren Fiona Fetch
John - 0 0 0 3 0 0 0 2 3
Ken 0 - 0 0 0 1 1 0 0 0
Smith 1 0 - 0 0 2 0 1 0 0
Jacky 0 0 0 - 3 0 0 3 0 0
Carl 0 1 0 0 - 0 0 0 2 0
Winnie 0 0 0 3 3 - 0 0 0 0
Will 0 3 2 0 3 0 - 0 2 0
Daren 0 0 0 3 3 0 0 - 0 0
Fiona 0 0 1 0 3 0 0 0 - 0
Fetch 0 0 0 3 3 0 0 0 0 -
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Sociocentric Network Approach• What if the population of interest is over 100 or 1,000?• For
– 30 actors there would be 435 (undirected) or 870 (directed) interactions
– 100 actors there would be 4950 (undirected) or 9900 (directed) interactions
• Scrutinising through long lists of names and identifying multiplex ties with actors on the list causes fatigue and recall problems (Bernard et al, 1982)
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Egocentric Network Approach (..cont)• “Ego” is the actor we are interested in. “Alters” are the
people referred to by the ego as having a tie with• Coleman, Katz et al’s (1957) medical innovation diffusion
study adopted egocentric approach from doctors– To whom did you turn to for advice and information?– With whom did you most often discuss cases in an ordinary week?– Who were the friends between your colleagues whom you saw
often socially?
Ego
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Egocentric Network Approach (..cont)• Socio-demographic attribute data: Sex, Marital Status,
Education• Occupational attribute data: Age, professional
associations, social associations, journals read• Relational data: Density, Centrality and Centralisation
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Social Networks Correlates to Coordination
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Introduction to Enron Dataset
• We used the Enron Email Dataset to study the correlation between centrality and coordinative ability.
• The Enron Dataset is:– A collection of over 250,000 emails…– of about 150 employees…– from a real organisation…– over a period of 3.5 years
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Enron Email Corpus versions• Various instances of the email corpus:
– Federal Energy Regulatory Commission (619,449 emails, 158 employees)
– Stanford Research Institute then rectified data integrity problems
– Cohen (CMU) made the dataset public (517,431 emails, 151 addresses)
– Corrada-Emmanuel (250,484 emails, 149 users)
– Shetty and Adibi (252,759 emails, 151 users)
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Visualisation of Enron Communication Network1997-2002
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Preliminary Results of Enron Communication Network (1997-98)
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Preliminary Results of Enron Communication Network (1999)
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Preliminary Results of Enron Communication Network (2000)
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Preliminary Results of Enron Communication Network (2001)
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Preliminary Results of Enron Communication Network (2002)
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Research Framework
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Methodology summary– The methodology of the study involves four
research phases:• extraction and cataloguing of coordination
key phrases• calculation of coordination score bounded by
project scope• construction of social network matrices
using the centrality measures• hypothesis testing of the association
between network centrality and coordination
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Text Mining for Coordination
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Key Phrase Extraction
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Calculating Coordination Weights
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Text Mining and Coordination ScoreA text-mining application was created to deploy the model to
calculate coordination score from the Enron dataset.
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Social Network Matrices and Centrality• Measurement:
– Degree– Closeness– Betweenness
• Directional Analysis:– In-Centrality– Out-Centrality
UCINET 6 Output of Closeness
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Project Based Coordination Results• Coordination and centrality across three projects
The coordination and centrality scores are ranked.6 of the 8 cases ranked equally.
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Organisational Position and CoordinationEmployee title and role, along with coordination and centrality scores
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Mapping average coordination against position in organisational hierarchy
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Results Summary
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