Actor Centrality Correlates to Project based Coordination

Liaquat Hossain, Ph.D.

Knowledge Management Research Lab Email: lhossain@it.usyd.edu.au

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Agenda

• Introduction to Social Networks

• Visualising & Interpreting Social Networks

• Social Network Data Collection & Analysis

• 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

0

1

2

3

4

5

6

7

8

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

Nu

mb

er

of

Pap

ers

Pu

bli

sh

ed

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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Visualising & Interpreting Social Networks

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Collaboration Network

Source: Otte & Rousseau (2002)

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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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Enron Email Communication Corpus

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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 ExtractionKey Phrase Extraction

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Calculating Coordination WeightsCalculating Coordination Weights

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Text Mining and Coordination Score

A text-mining application was created to deploy the model to A text-mining application was created to deploy the model to calculate coordination score from the Enron dataset.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 UCINET 6 Output of ClosenessCloseness

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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 Employee title and role, along with coordination and centrality scores.centrality scores.

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Mapping average coordination against Mapping average coordination against position in organisational hierarchyposition in organisational hierarchy

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Results SummaryResults Summary