The document discusses a study that examines the correlation between actor centrality in social networks and their ability to coordinate projects. It outlines the research framework, which involves extracting coordination-related phrases from emails, calculating coordination scores bounded by project scopes, constructing social network matrices using centrality measures, and testing the association between centrality and coordination. Preliminary results on the Enron email network from 1997-2002 are presented. The methodology involves text mining the Enron dataset to calculate coordination scores and social network centrality metrics like degree, closeness, and betweenness centrality.

1. Actor Centrality Correlates to Project based Coordination Liaquat Hossain, Ph.D. Knowledge Management Research Lab Email: lhossain@it.usyd.edu.au

2. 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

3. Introduction to Social Networks

4. 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)

5. Growth of Social Networks Social Networks research has been growing exponentially over the past decades Source: Otte & Rousseau (2002)

6. Distribution of Social Network Research

7. At the Beginning of the Hype Curve Source: IBM (2005)

8. Visualising & Interpreting Social Networks

9. Collaboration Network Source: Otte & Rousseau (2002)

10. Sexual relations Colorado Spring data By Gender (Morris, Moody et al.) Male Female

11. Social Network Data Collection & Analysis

12. 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

13. An Adjacency Matrix - 0 0 0 0 3 3 0 0 0 Fetch 0 - 0 0 0 3 0 1 0 0 Fiona 0 0 - 0 0 3 3 0 0 0 Daren 0 2 0 - 0 3 0 2 3 0 Will 0 0 0 0 - 3 3 0 0 0 Winnie 0 2 0 0 0 - 0 0 1 0 Carl 0 0 3 0 0 3 - 0 0 0 Jacky 0 0 1 0 2 0 0 - 0 1 Smith 0 0 0 1 1 0 0 0 - 0 Ken 3 2 0 0 0 3 0 0 0 - John Fetch Fiona Daren Will Winnie Carl Jacky Smith Ken John Seeks advice from

14. 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)

15. 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

16. 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

17. Enron Email Communication Corpus

18. 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

19. 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)

20. Visualisation of Enron Communication Network 1997-2002

21. Preliminary Results of Enron Communication Network (1997-98)

22. Preliminary Results of Enron Communication Network (1999)

23. Preliminary Results of Enron Communication Network (2000)

24. Preliminary Results of Enron Communication Network (2001)

25. Preliminary Results of Enron Communication Network (2002)

26. Research Framework

27. 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

28. Text Mining for Coordination

29. Key Phrase Extraction

30. Calculating Coordination Weights

31. Text Mining and Coordination Score A text-mining application was created to deploy the model to calculate coordination score from the Enron dataset.

32. Social Network Matrices and Centrality Measurement: Degree Closeness Betweenness Directional Analysis: In-Centrality Out-Centrality UCINET 6 Output of Closeness

33. Project Based Coordination Results Coordination and centrality across three projects The coordination and centrality scores are ranked. 6 of the 8 cases ranked equally.

34. Organisational Position and Coordination Employee title and role, along with coordination and centrality scores.

35. Mapping average coordination against position in organisational hierarchy

36. Results Summary