1. Who’s in Your School Learning Community Network? Barbara Schultz-Jones, PhD Department of Library and Information Sciences College of Information University of North Texas Denton, TX ESC Region XI Virtual Technology Conference November 10, 2009

2. 11/10/09Schultz-Jones / ESC XI2 Agenda Show me your network Background Social network theory Social network analysis Texas schools Constructing a social network Applications of this approach

3. 11/10/09Schultz-Jones / ESC XI3 Social Networking

4. 11/10/09Schultz-Jones / ESC XI4 Background The application of social network theory to the study of groups and group dynamics has its roots in the 1930s and the formulation of sociometry (Moreno, 1934). Textile metaphors of fabric and web were used to describe interweaving relations of social action (1950 – 1970) Diverse traditions culminated in the current use of social network analysis: anthropology, psychology, sociology and mathematics.

5. 11/10/09Schultz-Jones / ESC XI5 Social network theory Seeks to explain the workings of networks Small-world method (Milgram, 1967) 6 degrees of separation (the Kevin Bacon Game) Two prominent network properties provide a framework for viewing network behavior: the strength of weak ties (Granovetter, 1973, 1983) structural holes (Burt, 1992)

6. 11/10/09Schultz-Jones / ESC XI6 Social network example

7. 11/10/09Schultz-Jones / ESC XI7 Social network analysis The methodology used to research network behavior The network diagram, or sociogram, is a crucial means to demonstrate and illustrate the concepts, despite the limitations to its use by the difficulties of illustrating networks of high density. In order to apply the concepts regarding the behavior of networks it is essential to identify the roles and positions of the members of the network. The members of a network may be people, things or concepts depending on the focus of the analysis.

8. 11/10/09Schultz-Jones / ESC XI8 Who uses this approach? Seven disciplines: business and management computer science humanities information science medicine and health sciences social sciences

9. 11/10/09Schultz-Jones / ESC XI9 Network approaches Citation analysis Diffusion of information Information flow Degree of contact/interaction Role and position analysis

10. 11/10/09Schultz-Jones / ESC XI10 How does this apply to the school learning environment? Demonstrated levels of connectivity: Between individuals Within and between departments Assessment tool for group interaction Analysis tool for students

11. 11/10/09Schultz-Jones / ESC XI11 Frequency of Interaction SLMS 1 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

12. 11/10/09Schultz-Jones / ESC XI12 Level of Interaction SLMS 1 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

13. 11/10/09Schultz-Jones / ESC XI13 Frequency of Interaction SLMS 2 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

14. 11/10/09Schultz-Jones / ESC XI14 Level of Interaction SLMS 2 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

15. 11/10/09Schultz-Jones / ESC XI15 Frequency of Interaction SLMS 3 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

16. 11/10/09Schultz-Jones / ESC XI16 Level of Interaction SLMS 3 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

17. 11/10/09Schultz-Jones / ESC XI17 Frequency of Interaction SLMS 4 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

18. 11/10/09Schultz-Jones / ESC XI18 Level of Interaction SLMS 4 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

19. 11/10/09Schultz-Jones / ESC XI19 Frequency of Interaction SLMS 5 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

20. 11/10/09Schultz-Jones / ESC XI20 Level of Interaction SLMS 5 Blue – Language Arts Green – Math/Science Purple – History/Foreign Lang. Yellow – Administration Red - SLMS

21. 11/10/09Schultz-Jones / ESC XI21 Frequency of Interaction 2 Schools - Science

22. 11/10/09Schultz-Jones / ESC XI22 Terminology Network: an interconnected system Node/actor/social entity: “discrete individual, corporate or collective social units” (Wasserman & Faust, 1999, p.17) Level of analysis/discussion: Egocentric: single node as the focus of attention Whole: consideration of all nodes in the environment Ties: the relationship connection between pairs of nodes/actors/entities: Content: the resource shared, delivered or exchanged Directed/Asymmetrical: content flows in one direction Reciprocal/Symmetrical: content flows in both directions Undirected: physically proximate but no exchange, or the exchange is not considered relevant to the research question Strong: close association, based on the research context Weak: distant association, based on the research context

23. 11/10/09Schultz-Jones / ESC XI23 How is data gathered? Social network map – an instrument developed by Todd (cited in Curtis, 1979) Surveys and interviews – personal or group network surveys that identify information exchange connections (Cross & Parker, 2003) Agent-based technology to capture email and document flow across servers Metrics of journals, authors, citations, co-citations, websites, online community positions

24. 11/10/09Schultz-Jones / ESC XI24 How is the data analyzed? Construct a matrix identifying connections between nodes/actors/individuals

25. 11/10/09Schultz-Jones / ESC XI25 How is the data analyzed? Employ software programs: GraphPlot: a spreadsheet and a drawing tool for sociometric data KrackPlot: a network graphics computer program. Social Network Analysis Functional Utility (SNAFU): MacOS network analysis and algorithm development software Social Network Visualizer for Linux (SocNetV): a GNU program for Linux OS to visualize graphically and play with social networks UCINET: a general program designed to facilitate the analysis of social network data (Borgatti & Freeman, 2002) http://www.analytictech.com/networks/ Pajek: a network drawing package; large density networks

26. 11/10/09Schultz-Jones / ESC XI26 Practical Demonstration Sign-up sheet of attendees Distribute list and ask each attendee to identify if they have met any other attendees Compile results in a matrix Input matrix to UCINET software program Produce sociogram of attending network Discuss results

27. 11/10/09Schultz-Jones / ESC XI27 Classroom applications Math Calculate distances between contacts Science Map the connections between countries and animal species English Map the connections between authors (Shakespeare, for example), and derivative works (the movie Shakespeare in Love, for example).

28. 11/10/09Schultz-Jones / ESC XI28 Future applications Within a subject area Within a school Within a district Within a state Within a region Anywhere the degree or frequency of connectivity is important

29. 11/10/09Schultz-Jones / ESC XI29 Thank You! If you have any interest in exploring future applications of social network analysis Please contact me: Barbara.Schultz-Jones@unt.edu

30. 11/10/09Schultz-Jones / ESC XI30 References Borgatti, S.P., Everett, M.G. & Freeman, L.C. (2002). Ucinet for Windows: Software for social network analysis. Harvard, MA: Analytic Technologies. Burt, R.S. (1992). Structural holes: The social structure of competition. Cambridge, MA: Harvard University Press. Cross, R. & Parker, A. (2003). The hidden power of social networks: Understanding how work really gets done in organizations. Boston, MA: Harvard Business School Press. Granovetter, M.S. (1973). The strength of weak ties. American Journal of Sociology, 78, 1360-1380.

31. 11/10/09Schultz-Jones / ESC XI31 References (cont.) Granovetter, M.S. (1983). The strength of weak ties: A network theory revisited. Sociological Theory, 1, 201-233. Moreno, J.L. (1934). Who shall survive? New York: Beacon Press. Schultz-Jones, B. (2009). Collaboration in the school social network: School library media specialists connect. Knowledge Quest, 37(4), 20-25. Wasserman, S. & Faust, K. (1999). Social network analysis: Methods and applications. New York: Cambridge University Press.