University of Technology Sydney

42913 Social and Information Network Analysis

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2024 is available in the Archives.

UTS: Information Technology: Computer Science
Credit points: 6 cp

Subject level:

Postgraduate

Result type: Grade and marks

Requisite(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 ((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. Understand basic concepts in social and information networks. (D.1)
2. Use important metrics and models to characterize networks. (D.1)
3. Utilize software tools to visualize real-life network data. (D.1)
4. Apply the concepts and techniques learned in class to analyse networks of their interest. (D.1)
5. Understand behaviour of social and information networks. (D.1)
6. Communicate in the form of technical report. (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 4

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

D.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, 4 and 5

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

D.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, 4, 5 and 6

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, 4 and 5

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

D.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