- Code SOCY8014
- Unit Value 6 units
- Offered by Australian Demographic & Social Research Institute
- ANU College ANU College of Arts and Social Sciences
- Course subject Sociology
- Areas of interest Political Sciences, Social Research, Sociology, Demography, Criminology
- Academic career PGRD
- Mode of delivery In Person
The world is inherently "networked" and social network analysis provides a rigorous framework for understanding how the structure of relations, in addition to the attributes of individual actors, determine behaviour and outcomes. Via this course, students learn about the network perspective and how to apply it to answer important questions in various fields in social science. The course teaches students a range of social network analysis techniques, provides training in social network analysis software and students work on an independent research project.
Upon successful completion, students will have the knowledge and skills to:
Upon Successful completion of this course, students will be able to:
- Understand a broad range of network concepts and
- Appreciate how network analysis can contribute to
increasing knowledge about diverse aspects of society.
- Use a relational approach to answer questions of interest
to them (i.e. be able to apply 'network thinking').
- Analyse social network data using various software
- Present results from social network analysis, both orally and in writing.
Problem set 1 (using NodeXL) (10%) (750 words equiv.) - LO 1, 2, 4
Problem set 2 (using R statistical software) (20%) (1500 words equiv.) - LO 1, 2, 4
Oral presentation of research project (10%) (20 minutes) - LO 1-5
Final paper for research project (60%) (4500 words) - LO 1-5
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3 hours of contact time (mixture of lectures, seminars and computer labs) per week for 13 weeks. Students are expected to undertake a further 7 hours per week of independent study over the semester (total 130 hours).
Requisite and Incompatibility
Prescribed TextsNotes will be provided.
Some prior exposure to introductory social network analysis, via courses such as SOCR8005 Social Science of the Internet, SOCR8006 Online Research Methods or equivalent courses. Prior exposure to statistical programming e.g. R or Stata.
Tuition fees are for the academic year indicated at the top of the page.
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- Student Contribution Band:
- Unit value:
- 6 units
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- International fee paying students
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