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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

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DRPS : Course Catalogue : School of Social and Political Science : Sociology

Postgraduate Course: Social Network Research: Theories and Analysis (SCIL11042)

Course Outline
SchoolSchool of Social and Political Science CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryArticulating social network theory and methods, this course seeks to explore the transformations of social life in contemporary societies characterized by the importance of connectedness and geographic mobility. The course will introduce students to the theories, concepts and measures of social network analysis (SNA) through a mixture of classroom teaching and hands-on computer work. It aims to discuss in particular: (1) to what extent social life is more networked in late modern societies; (2) how SNA is a powerful way of capturing empirically social life; (3) to what extent social networks are more individualized; (4) how physical and virtual mobility play an increasing role in meetings and social relationships. Key notions will be addressed and illustrated through both the discussions of major thinkers and the use of the UCINet software and its visualization program NetDraw on real-world data sets. Emphasis will be placed on sociological/social science research, even though students will be free to choose their own topic/discipline for their final essay. No prior knowledge of social network analysis, math or statistics is assumed for this course.
Course description A powerful way of making sense of the complexity of the social world is to analyse connections between people, groups and objects as social networks. Friendship, love, ideas, money, power or disease pass through and are shaped by networks. This course will introduce you to the key concepts and measures of social network analysis (SNA) through a mixture of classroom teaching and hands-on computer work. We will use UCINet and Gephi as SNA software packages for network analysis and visualisation.

Articulating social theory and social network research, it will get you thinking about the transformations of social life in contemporary societies characterised by the importance of connectedness and spatial mobility. Although individuals have substantial leeway in building their social relationships, we will show that the size, composition, geography and structure of their social networks are not random but follow some rules that SNA can reveal empirically.

Emphasis will be placed on social science research, but students will be encouraged to choose their own topic and discipline for their final essay. No prior knowledge of social network analysis, maths or statistics is assumed for this course.


Outline Content

Lecture 1: SNA: exploring social relationships in contemporary societies
In this session we will discuss contemporary changes in the ways people relate to each other and the key principles of social network research.

Lab session 1: Starting with UCINet: Importing, visualising and transforming network data
In this lab session we will learn how to collect, import, visualise and transform real-world network data using UCINet 6 and NetDraw visualisation software.

Lecture 2: Social capital and social inequalities
In this session the two forms of social capital - bonding and bridging social capital - will be discussed through the work of Ronald Burt, James Coleman, Mark Granovetter, Nan Lin and Robert Putnam.

Lab session 2: Analysing the network cohesion: density, reciprocity and transitivity
In this session we will start analysing networks at three different levels of analysis: the network level (density), the dyadic level (reciprocity) and the triadic level (transitivity).

Lecture 3: Small world and communities
How many and what people do we know? How many intermediaries, on average, do we need to reach anyone on this planet? In this lecture, we will provide some answers to these fundamental questions about social life in mobile and globalised societies.

Lab session 3: Analysing power and prestige: centrality measures
This session examines the relational approach of power and the different network measures of centrality.

Lecture 4: Networks over time and space
This session explores how networks change over the life course and across space. We will discuss the issue of social life in the context of increasing spatial mobility requirements and behaviours.

Lab session 4: Detecting communities: cohesive subgroup analysis
In this session we will learn how to detect and interpret communities (cohesive subgroups).

Lecture 5: Mixing methods in social network research & Conclusion
In this session we will return to the agency-structure and network-institution interplay raised at the beginning of the course. We will also discuss mixing methods in social network research.

Lab session 5: Analysing affiliation networks
In this session we will learn how to analyse affiliation (or two-mode) networks to capture the agency-structure duality.


The course is hands-on, taught through lectures and computer lab sessions. You will conduct your own research using social network analysis and write it up for your final essay. It is taught through in-class activities and practical exercises in lab. I encourage you to make connections between theory and social network research. The course is cross-discipline and open to students with backgrounds in social sciences, natural sciences and the humanities.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
Pre-requisitesNone
High Demand Course? Yes
Course Delivery Information
Academic year 2022/23, Available to all students (SV1) Quota:  26
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Seminar/Tutorial Hours 20, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 176 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Two 750-word practical exercises, worth 30% of the total mark, «br /»
One 3,000 word essay (appendices and bibliography excluded), worth 70% of the total mark), where students will collect their own network data or use a pre-existing dataset to critically address a research question in a discipline of their choosing..
Feedback The course will include formative feedback through weekly exercises in lab. The exercises will be technically oriented to ensure that you have a good command of the software packages. But I encourage you to reflect on lectures and readings to discuss the results. The assessment of the weekly exercises provide students with formative feedback for their final essay.
An additional session will be organised to discuss your final essay topic with the Course Organiser, either individually or within small groups. We will discuss data access and how to develop a meaningful research question using social networks.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate a critical understanding of the key concepts and principles of social network analysis
  2. Use an appropriate SNA software package to critically examine important issues in the field of social network analysis
  3. Develop extensive, detailed and critical knowledge and understanding in one area of social network analysis linked to a discipline of their choosing
  4. Write a detailed report to communicate the results of a small-scale research project using SNA in a chosen discipline
Reading List
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Castells, M. (2000). The rise of the network society. Blackwell, Oxford.
Finch, J. Mason, J. (1993). Negotiating family responsibilities. New York: Routledge.
Fischer, C. S. (1982). To Dwell Among Friends: Personal Networks in Town and City. Chicago: University of Chicago Press.
Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91, 481-510.
Heider, F. (1946). Attitudes and cognitive organization. Journal of Psychology, 21, 107-112.
Heider, F. (1958). The psychology of interpersonal relations. New York: Wiley.
Kadushin, C. (2011). Understanding social networks: Theories, concepts, and findings. Chapter 1. Oxford University Press, USA.
Rainie, L. Wellman, B. (2012). Networked: The new social operating system. MIT Press.
Scott, J. (2012). What is social network analysis? Bloomsbury Academic. Chapter 2.
Urry, J. (2003). Social networks, travel and talk. British Journal of Sociology, 54, 155-175.
Urry, J. (2012). Social networks, mobile lives and social inequalities. Journal of Transport Geography, 21, 24-30.
Van Dijk, J. (1999). The network society: Social aspects of new media. Sage.
Wellman, B. Berkowitz, S.D. (Eds.) (1988). Social Structures: A Network Approach. Cambridge: Cambridge University Press.
Wellman, B. (2001). Physical place and cyberspace: The rise of personalized networking. International Journal of Urban and Regional Research, 25, 227-252.
De Nooy, W. Mrvar, A. Batagelj, V. (2005). Exploratory social network analysis with Pajek. Chapters 1-2. Cambridge: Cambridge University Press.
Hanneman, R. A. Riddle, M. Introduction to social network methods. Chapters 1-5 and 7-8. http://faculty.ucr.edu/~hanneman/nettext/
Kadushin, C. (2011). Understanding social networks: Theories, concepts, and findings. Chapters 2-3. Oxford University Press, USA.
Knoke, D. Yang, S. (2007). Social Network Analysis. Quantitative Applications in the Social Sciences. Chapters 1-4. Thousand Oaks, California: Sage.
Scott, J. (2012). Social network analysis. 3rd Edition. Chapters 1-4. London: Sage Publications.
Wasserman, S. Faust, K. (1994). Social Network Analysis: Methods and Applications. Chapters 1-2 and 4. Cambridge: Cambridge University Press.
Burt, R. S., 1992. Structural holes: The social structure of competition. Harvard University Press, Cambridge, MA.
Burt, R. S. (2005). Brokerage and closure: An introduction to social capital. Oxford: Oxford University Press.
Coleman, J. S. (1988). Social Capital in the Creation of Human Capital. American Journal of Sociology, 94(S1), 95-120.
Crossley, N. (2008). (Net)working out: social capital in a private health club. The British journal of sociology, 59, 475-500.
Edwards, R. Franklin, J. Holland, J. (2003). Families and social capital: exploring the issues. London: South Bank University.
Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360-1380.
Kadushin, C. (2011). Understanding social networks: Theories, concepts, and findings. Chapter 10. Oxford University Press, USA.
Knoke, D. (2001). Changing Organizations: Business Networks in the New Political Economy. Boulder: Westview.
Lin, N. (1999). Building a network theory of social capital. Connections, 22, 28-51.
Lin, N. (2001). Social capital. A theory of social structure and action. Cambridge University Press, New York.
Lin, N. Cook, K. S. Burt, R. S. (2001). Social capital: theory and research. Aldine de Gruyter.
Putnam, R. D. (2000). Bowling alone. New York: Simon & Schuster.
Bonacich, P. (1987). Power and Centrality: A Family of Measures. American Journal of Sociology, 92, 1170-1182.
De Nooy, W. Mrvar, A. Batagelj, V. (2005). Exploratory social network analysis with Pajek. Chapters 6-7 and 9. Cambridge: Cambridge University Press.
Hanneman, R. A. Riddle, M. Introduction to social network methods. Chapters 9-10. http://faculty.ucr.edu/~hanneman/nettext/
Ibarra, H. (1993). Network centrality, power and innovation involvement: Determinants of technical and administrative roles. Academy of Management Journal, 36, 471-501.
Kadushin, C. (2011). Understanding social networks: Theories, concepts, and findings. Chapter 3. Oxford University Press, USA.
Knoke, D. Yang, S. (2007). Social Network Analysis. Quantitative Applications in the Social Sciences. Chapter 4. Thousand Oaks, California: Sage.
Krackhardt, D. (1999). Ties that torture: Simmelian tie analysis in organizations. Research in the Sociology of Organizations, 16, 183-210.
Krackhardt, D. Porter, L. W. (1985). When friends leave: A structural analysis of the relationship between turnover and stayers¿ attitudes.¿ Administrative Science Quarterly, 30, 242-261.
Scott, J. (2012). Social network analysis. 3rd Edition. Chapter 5. London: Sage Publications.
Wasserman, S. Faust, K. (1994). Social Network Analysis: Methods and Applications. Chapters 5-6. Cambridge: Cambridge University Press.
Barabási, A.-L. (2003) Linked. New York: Plume.
Bell, C. Newby, H. (1971). Community Studies. London: Allen and Unwin.
Bidart, C. Lavenu, D. (2005). Evolutions of personal networks and life events. Social Networks, 27, 359-376.
Christakis, N. A. Fowler, J. H. (2007). The Spread of Obesity in a Large Social Network over 32 Years. New England Journal of Medicine, 357, 370-379.
Small animation here: http://www.nejm.org/doi/full/10.1056/NEJMsa066082
Crossley, N. (2008). Small-world networks, complex systems and sociology. Sociology, 42, 261-277.
Crossley, N. (2009). The man whose web expanded: Network dynamics in Manchester's post/punk music scene 1976¿1980. Poetics, 37, 24-49.
Crow, G. Maclean, C. (2006) Community. In Payne, G. (Ed.). Social divisions. (pp. 305¿324), Basingstoke: Palgrave Macmillan.
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Feld, S. (1981). The focused organisation of social ties. American Journal of Sociology, 86: 1015-1035.
Feld, S. (1982). Social structural determinants of similarity among associates, American Sociological Review 47, 797-801.
Fischer, C. S. (1982). To Dwell Among Friends: Personal Networks in Town and City. Chicago: University of Chicago Press.
Guare, J. (1990). Six Degrees of Separation: A Play. New York: Vintage.
Kadushin, C. (2011). Understanding social networks: Theories, concepts, and findings. Chapter 8. Oxford University Press, USA.
Milgram, S. (1967). The Small World Problem, Psychology Today, 2, 60-67.
Scott, J. (2012). Social network analysis. 3rd Edition. Chapter 8. London: Sage Publications.
Simmel, G. (1955 [1908]). The web of group affiliations. In: Conflict and the web of affiliations. Trans. R. Bendix. New York: Free Press, pp. 125-195.
Watts, D. J. (2003). Small worlds: the dynamics of networks between order and randomness. Princeton: Princeton University Press.
Watts, D. J. (2004). Six Degrees. London: Vintage.
Watts, D. J. Strogatz, S. H. (1998). Collective Dynamics of Small-World Networks. Nature, 393, 440-442.
Wellman, B. Carrington, P.J. Hall, A. (1988). Networks as personal communities. In Wellman, B., Berkowitz, S.D. (Eds.). Social Structures: A Network Analysis. Cambridge: Cambridge University Press.
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De Nooy, W. Mrvar, A. Batagelj, V. (2005). Exploratory social network analysis with Pajek. Chapter 3. Cambridge: Cambridge University Press.
Hanneman, R. A. Riddle, M. Introduction to social network methods. Chapter 11. http://faculty.ucr.edu/~hanneman/nettext/
Kadushin, C. (2011). Understanding social networks: Theories, concepts, and findings. Chapter 4. Oxford University Press, USA.
Knoke, D. Yang, S. (2007). Social Network Analysis. Quantitative Applications in the Social Sciences. Chapter 4. Thousand Oaks, California: Sage.
Scott, J. (2012). Social network analysis. 3rd Edition. Chapter 6. London: Sage Publications.
Wasserman, S. Faust, K. (1994). Social Network Analysis: Methods and Applications. Chapter 7. Cambridge: Cambridge University Press.
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Rainie, L. Wellman, B. (2012). Networked: The new social operating system. MIT Press.
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Additional Information
Graduate Attributes and Skills Students will develop the skills to:
- Work independently on a research question of their choosing;
- Analyse network/quantitative data and display the results graphically to support their argumentation;
- Write a well-argued essay, based on empirical evidence;
- Develop an original and creative response to complex research questions.
KeywordsNot entered
Contacts
Course organiserDr Tod Van Gunten
Tel: (0131 6)50 4637
Email: tvangun@exseed.ed.ac.uk
Course secretaryMrs Beth Richardson-Mills
Tel: (0131 6)51 1659
Email: brichar3@ed.ac.uk
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