Computational Methods for Network Science covers the essentials of using computational approaches to pose and answer social science research problems. In doing so it also covers a selected set of network algorithms in depth. This includes random graph models, homophily and friendship paradox, influence and contagion in networks, markets and network games, network resilence. Furthermore, it also teaches students about the ethics of doing data-driven social science research.
The course equips the students with in-depth knowledge and hands-on experience in working with network data to study social processes at both the individual and aggregate levels. Graduates will be equipped with the technical, theoretical and conceptual skills and knowledge to start a budding career in this field of research.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Demonstrate a thorough understanding of the fundamental principles of using computational approaches to formulate and answer social science questions.
- Demonstrate a working understanding in the ethical concerns of data drive analysis and experiments in human behavior.
- Apply network analysis algorithms in practical contexts.
- Analyze results from network algorithms, and articulate their limitations.
- Communicate the process of formulating and solving computational social science problems to a team of professionals with computing and/or social sciences.
Indicative Assessment
- Assignments (40) [LO null]
- Project (40) [LO null]
- Final Examination (20) [LO null]
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Workload
Up to 60 hours of total face-time, which includes interactions with lectures and tutors. Up to 60 hours of total preparation, repeat, assignment and practical exercise time.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
Not required
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2023 | $4860 |
- International fee paying students
| Year | Fee |
|---|---|
| 2023 | $6180 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 4205 | 19 Feb 2024 | 26 Feb 2024 | 05 Apr 2024 | 24 May 2024 | In Person | View |
