- UCAS course code
- S456
- UCAS institution code
- M20
BASS Social Anthropology and Data Analytics / Course details
Year of entry: 2024
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Course unit details:
Connections matter: Sociological Applications of Social Networks
Unit code | SOCY30292 |
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Credit rating | 20 |
Unit level | Level 3 |
Teaching period(s) | Semester 2 |
Available as a free choice unit? | Yes |
Overview
This unit is an introduction to the applications of social network analysis in sociological research. We discuss the theoretical perspectives of social networks as they have been applied in various substantive areas, the main techniques of data collection and analytical strategies that can be used to understand structural opportunities and constrains for individual action. Each lecture then focuses on a specific area of application, like personal networks and community studies, occupational structure, criminal networks, scientific networks, migration networks, health and interventions, and inequalities in networks. No preliminary knowledge of social network analysis is required: the module does not focus on methods, but illustrate research examples that use SNA in empirical sociological studies.
Aims
How do terrorist networks work? Do communities survive in individualistic societies? How do migrants decide to leave their countries and settle elsewhere? How do innovations diffuse? Why women have different networks, and different life outcomes, compared to men? These are the kind of sociological questions that social network analysis can help to answer.
Social network analysis techniques are normally used to analyse the social relationships between individuals, or individuals' aggregate (groups, organizations, nations). In this sense, a network is the formal representations of actors (nodes) who are in some sort of relationship (ties) with each other, where relationships can be broadly defined to include a vast variety of social connections, from friendship to transmission of diseases. Social networks can thus be observed in a variety of contexts, and they have been applied in several sociological areas, where they have modified and sometimes improved our understanding of social phenomena. The aim of the course is to familiarize students with some of the core areas in social network research, and to stimulate a critical debate on the benefits and limits of this perspective.
Learning outcomes
On completion of this unit successful students will be able to:
- Understand the influence of social connections on individual behaviour (in practices like criminal behaviour, organizations' performances, addictive behaviours, neighbourhood relationships, and the like).
- Appreciate the benefits and limits of using a social networks approach in several sociological areas of research, like sociology of science, sociology of personal relationships, community studies, sociology of health, criminology, sociology of culture.
- Understand the peculiarity of social network perspective, and critically engage with relational and analytical theories.
- Be familiar with social networks research design and data collection in several sociological areas.
Syllabus
- WHAT IS SOCIAL NETWORK ANALYSIS?
- SOCIAL NETWORK THEORIES
- COMMUNITY, URBANIZATION, AND PERSONAL NETWORK
- SOCIAL CAPITAL, OCCUPATIONAL STRUCTURE AND STRATIFICATION
- GENDER AND INEQUALITIES IN NETWORKS
- MIGRATION NETWORKS
- DIFFUSION NETWORKS AND HEALTH INTERVENTIONS
- CULTURAL NETWORKS
- COVERT NETWORK
- SCIENTIFIC NETWORKS
Teaching and learning methods
Main ideas will be presented in an hour weekly lecture, followed by a workshop session. Each week a reading on a topic will be assigned: students will be advised to read suggested readings and slides before the lectures to stimulate the discussion and questions. In workshops students will be asked to sit in groups and perform practical tasks related to the topics discussed in the previous lecture. In some weeks, students will be asked to do some simple homework that will be the basis of the workshops' practical tasks. The course does not expect students to learn how to do formal network analysis, but to simply appreciate how studies can be conducted, the advantages they offer, and how results can be interpreted. Materials will be available on blackboard.
The module requires that you study for a minimum of 12 hours per week. This is comprised of teaching and independent study in these proportions: • 3 hours lectures and tutorials
- At least 3 hours reading the Key Reading;
- At least 3 hours reading an additional text from the reading list;
- At least 3 hours written work for assessed and non-assessed assignments.
This leaves 80 hours study time remaining to be used in independent study over the duration of the course.
Assessment methods
Non-assessed mid-term coursework submission (500 words)
Written coursework (2500 words, 100%)
Feedback methods
- Informal verbal formative feedback will be given during lectures and tutorials. (You'll need to contribute regularly to group discussions to make the best use of this.)
- Written formative feedback will be given on your non-assessed assignment and made available via Turnitin. Half a day individual feedback discussion will be available in the lecturer's office.
- Written formative and summative feedback will be given on your assessed coursework, available via Turnitin. Half a day individual feedback discussion will be available in the lecturer's office.
Recommended reading
Kadushin C., 2012, Understanding social networks, Oxford University Press, Oxford.
Robins, G. 2015. Doing Social Networks Research: Network Research Design for Social Scientists. Sage, London
Jackson M.O., 2019, The Human Network. New York: Pantheon Books.
Christakis N., Fowler J., 2009, Connected: The Amazing Power of Social Networks and How They Shape Our Lives. London: Harperpress.
Study hours
Scheduled activity hours | |
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Lectures | 30 |
Independent study hours | |
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Independent study | 168 |
Teaching staff
Staff member | Role |
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Elisa Bellotti | Unit coordinator |