Actor Centrality Correlates to Project based Coordination

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 Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

3. Introduction to Social Networks Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

5. Growth of Social Networks • Social Networks research has been growing exponentially over the past decades Source: Otte & Rousseau (2002) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

6. Distribution of Social Network Research Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

7. At the Beginning of the Hype Curve Source: IBM (2005) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

8. Visualising & Interpreting Social Networks Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

9. Collaboration Network Source: Otte & Rousseau (2002) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

10. Sexual relations Colorado Spring dataBy Gender (Morris, Moody et al.) Male Female Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

11. Social Network Data Collection & Analysis Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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 Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

13. An Adjacency Matrix Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

15. Ego 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? Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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 Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

17. Enron Email Communication Corpus Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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 Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

20. Visualisation of Enron Communication Network 1997-2002 Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

21. Preliminary Results of Enron Communication Network (1997-98) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

22. Preliminary Results of Enron Communication Network (1999) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

23. Preliminary Results of Enron Communication Network (2000) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

24. Preliminary Results of Enron Communication Network (2001) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

25. Preliminary Results of Enron Communication Network (2002) Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

26. Research Framework Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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 Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

28. Text Mining for Coordination Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

29. Key Phrase Extraction Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

30. Calculating Coordination Weights Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

31. Text Mining and Coordination Score A text-mining application was created to deploy the model to calculate coordination score from the Enron dataset. Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

32. Measurement: Degree Closeness Betweenness Directional Analysis: In-Centrality Out-Centrality Social Network Matrices and Centrality UCINET 6 Output of Closeness Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

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. Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

34. Organisational Position and Coordination Employee title and role, along with coordination and centrality scores. Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

35. Mapping average coordination against position in organisational hierarchy Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia

36. Results Summary Liaquat Hossain, Knowledge Management Research Lad, The University of Sydney, Australia