Social Network Analysis
Duration
- One semester or equivalent
Contact hours
- 30 Hours plus blended
On-campus unit delivery combines face-to-face and digital learning.
Aims and objectives
This unit aims to develop student's ability to understand the impact of social relationships in business, organisation and communities. Students will learn the theoretical foundations of social network analysis, design and conduct social network research in an applied way. Students will move from the fundamentals of networks to knowledge on how to use cutting-edge statical network models and software such as MPNet and VPNet, to gain deeper insights into network processes and improve business, organisational and community outcomes.
Unit Learning Outcomes (ULO)
On successful completion of this unit students will be able to:
1. Demonstrate coherent and advanced knowledge of social network theoretical concepts and their application
2. Critically analyse and synthesise network data available for an organisation/group
3. Apply knowledge of research principles and methods to design appropriate network research questions
4. Critically evaluate data and present an integrated and comprehensive report as a response to the identified research question
5. Apply team work knowledge and skills in effective collaboration across a range of complex activities and contexts during data analysis
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
Face to Face Contact Seminar | 24 | 1 | 24 |
Face to Face Contact Project | 6 | 1 | 6 |
Online Contact Directed Online Learning and Independent Learning | 6 | 1 | 6 |
Unspecified Learning Activities Independent Learning | 114 | 1 | 114 |
TOTAL | 150 hours |
Assessment
Types | Individual/Group Role | Weighting | Unit Learning Outcomes (ULOs) |
Assignment 1 | Individual | 0% | 1, 2, 3 |
| Assignment 2 | Individual | 0% | 1, 2, 3, 4 |
Presentation | Group | 0% | 1, 2, 3, 4, 5 |
| Report | Group | 0% | 1, 2, 3, 4, 5 |
Change to the assessment construction and weightings with more emphasis on individual assessment. This Phd Unit is run as a 5 day intensive workshop Assessment Range set to 0 as the unit is HED PASS only.
Content
- Introduction to Social Network Analysis (SNA)
- Stastistical Inference with network data
- Software for network visualistion and analysis
- Representing network data: Network Visualisation
- Networks in action: Case Studies
- Network Stastistical modelling using MPNet sofrware
- Assess key differences between analyses using tradional methods of SNA
Study resources
- Reading materials.
Reading materials
Students are advised to check the unit outline in the relevant teaching period for appropriate textbooks and further reading.