Analysing the Web and Social Networks

Unit code: ADM5004 | Study level: Postgraduate
(Generally, 1 credit = 10 hours of classes and independent study.)
City Campus
Online Real Time


Interconnected digital environments have the potential to disclose invaluable insights into the psychosocial attributes, expectations, and needs of users, and to influence future directions, through the collection and analysis of data. In this unit, we explore how to harness this data to inform decisions and the methodologies used in industry. We also deconstruct the notion of data and investigate using data on our own terms. A range of data sources, including metrics that are sometimes overlooked such as accessibility and sustainability metrics form part of our explorations. Learning analytics are a type of web analytics gaining importance for students and academics. We review the implications and the 'actionable insights' from this type of data.

Students will learn about analytical tools available to professionals, in particular, those that measure the performance of digital environments or products. They will learn how such tools inform research into the behaviour of users, product or service developments and improvements in campaign or project outcomes.

The unit is grounded in the consideration of the complexities in the field including those of trust, privacy, and information injustice.

Learning Outcomes

On successful completion of this unit, students will be able to:

  1. Formulate responsible, well-informed and ethical judgments in considering the role of the practitioner in a complex and highly dynamic digital media industry;
  2. Exhibit the ability for agile thinking in complex environments;
  3. Critically evaluate the strengths and limitations of industry standards as they apply to gathering information from digital environments; and
  4. Propose and resolve a professional web and social network analysis tasks.
  5. Participate in an academic community of discourse through reflective and critical engagement in academic texts and understanding of principles of academic integrity.


For Melbourne campuses

Hurdle assessment task: Completion of five Academic Integrity Modules

Assessment type: Case Study
Grade: 15%
A case study of data
Assessment type: Presentation
Grade: 40%
A series of strategies based on social network data and analysis
Assessment type: Report
Grade: 45%
A research report based on web data and analysis
Assessment type: Other
Grade: 0%
Evidence of completion of the Academic Integrity Modules

Required reading

Links to resources will be provided to students via VU Collaborate.

As part of a course

This unit is studied as part of the following course(s):

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