42913 Social and Information Network Analysis
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Credit points: 6 cp
Subject level:
Postgraduate
Result type: Grade and marksRequisite(s): (120 credit points of completed study in Bachelor's Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Honours Embedded owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Degree co-owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours co-owned by FEIT) AND 31250 Introduction to Data Analytics) OR ((24 credit points of completed study in 24.0000000000 Credit Points spk(s): C04380 Master of Business Analytics OR 48 credit points of completed study in 48.0000000000 Credit Points spk(s): C04379 Master of Business Analytics (Extension)) AND (32130 Fundamentals of Data Analytics OR 36106 Machine Learning Algorithms and Applications)
These requisites may not apply to students in certain courses. See access conditions.
Description
In social and economic lives, everything (e.g. people, information, business, events) is becoming more and more connected with the development of technologies such as social networks (e.g. Facebook, Twitter) and information networks (e.g. the Web). A practical way of making sense of these types of data is to analyse them as networks.
This subject introduces the students to basic concepts in social and information networks, metrics to characterise networks, models to explain the generation of networks, and methods to analyse networks. The students learn to use software tools to visualise and analyse real-world network data. The subject also introduces a wide variety of applications in social and information networks such as user recommendation and web search.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Analyse social and information networks with software tools to visualize real-life network data. (D.1) |
|---|---|
| 2. | Apply concepts in social and information networks with software tools to visualize real-life network data. (D.1) |
| 3. | Communicate social and information network analysis to a range of audiences. (E.1) |
| 4. | Collaboratively work as a team to produce design solution to complex problem. (E.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Technically Proficient: FEIT graduates apply theoretical, conceptual, software and physical tools and advanced discipline knowledge to research, evaluate and predict future performance of systems characterised by complexity. (D.1)
- Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating autonomously within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)
Contribution to the development of graduate attributes
Engineers Australia Stage 1 Competencies
This subject contributes to the development of the following Engineers Australia Stage 1 Competencies:
- 1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
- 1.4. Discernment of knowledge development and research directions within the engineering discipline.
- 2.1. Application of established engineering methods to complex engineering problem solving.
- 3.2. Effective oral and written communication in professional and lay domains.
- 3.4. Professional use and management of information.
Teaching and learning strategies
The material will be presented weekly over 1.5 hour lecture and 1.5 hour laboratory. Students will need to undertake preparation using material on UTSOnline to make effective use of their class time. There will also be assignments and a group project which will present aspects of the subject which depend on the material presented in seminars.
The subject takes an active learning approach in this subject and will receive feedback on their progress by completing zero-mark quizzes.
Students will engage in collaborative learning activities in the laboratories as well as in the group project. Other assessments will be individual work.
Content (topics)
- Basic concepts in social and information networks
- Graph metrics and models
- Network data visualization
- Network structure analysis
- Network dynamic analysis
- Web search
- Network mining
Assessment
Assessment task 1: Assignment 1 : Graph theory and network strucuture
| Intent: | To test understanding of the topics in the subject. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 3 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 15% |
| Length: | There is no word limit, but we expect assignments will be generally around 4-5 pages long. |
Assessment task 2: Assignment 2 : Network dynamics and information network
| Intent: | To test understanding of the topics in the subject. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 3 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 15% |
| Length: | There is no word limit, but we expect assignments will be generally around 4-5 pages long. |
Assessment task 3: Group Project : Social and information network related task
| Intent: | To apply the knowledge learned from the subject to analyse real-life network data of interest. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Project |
| Groupwork: | Group, group assessed |
| Weight: | 30% |
| Length: | Approximately 15-20 A4 pages (single space, including abstract and references) |
Assessment task 4: Final Exam
| Intent: | To test understanding of all topics in the subject. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2 and 3 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Examination |
| Groupwork: | Individual |
| Weight: | 40% |
| Length: | There is no word limit. |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more.
Required texts
D.Easley, J.Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press, 2010
References
M.Newman, Networks: An Introduction, Oxford University Press, 2010
S.P.Borgatti, M.G. Everett, J.C. Johnson, Analyzing Social Networks, SAGE Publications Ltd , 2013