Module POLM162 for 2019/0
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Postgraduate Module Descriptor
POLM162: Introduction to Social Network Analysis
This module descriptor refers to the 2019/0 academic year.
Module Aims
You will learn about the theories of social networks and how these ideas impact our understanding of other social science topics like political engagement, social capital, and deviance. We also discuss motivations for using social network analysis and the strengths and weaknesses of this approach in a variety of social science contexts. Using a combination of lectures, practical demonstrations and assignments, this module aims at developing your skills in the analysis and presentation of relational data. Specifically, you will learn multiple ways of formulating social network hypotheses and testing them using a combination of descriptive measures and inferential statistics. The course is taught using the programming language R. This course is only suitable for students who are either comfortable programming in R or currently learning R.
| On successfully completing the programme you will be able to: | |
|---|---|
| Module-Specific Skills | 1. Recognize and critically evaluate in writing the diversity of specialized techniques and approaches involved in analysing social network data in political science, sociology and criminology 2. Demonstrate advanced proficiency in the use of statistical analysis to test a social networks hypothesis 3. Show ability to present and summarize analysed data in an advanced, coherent, and effective manner 4. Demonstrate advanced proficiency in acquired skills, confidence and competence in a computer package for statistical analysis (the SNA package in R) |
| Discipline-Specific Skills | 5. Understand and demonstrate advanced proficiency in the use of the tools and techniques of social network analysis for political and social data 6. Use social network evidence to empirically evaluate the (relative) validity of political, sociological and criminological theories and hypothesis 7. Construct well thought out and rigorous data analysis, tables and reports for both written and oral presentation 8. Examine relationships between theoretical concepts with real world empirical data |
| Personal and Key Skills | 9. Demonstrate an ability to study independently 10. Demonstrate an advanced ability to deliver presentations to their peers, and communicate effectively in speech and writing 11. Use IT and, in particular, statistical software packages - for the retrieval, analysis and presentation of information |
How this Module is Assessed
In the tables below, you will see reference to 'ILO's. An ILO is an Intended Learning Outcome - see Aims and Learning Outcomes for details of the ILOs for this module.
Formative Assessment
A formative assessment is designed to give you feedback on your understanding of the module content but it will not count towards your mark for the module.
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Plan for final essay | Students can submit an abstract or outline for final assignment | 1-9 | Written |
Summative Assessment
A summative assessment counts towards your mark for the module. The table below tells you what percentage of your mark will come from which type of assessment.
| Coursework | Written exams | Practical exams |
|---|---|---|
| 90 | 0 | 10 |
...and this table provides further details on the summative assessments for this module.
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Problem sets | 30 | 3 x 500 words on analysis of a problem set | 3-8, 9, 11 | Written |
| Classroom presentation | 10 | 10 minute presentation on dataset for final paper | 3, 5, 6, 10 | Written |
| Final paper | 60 | 2000 words including an analysis component | 1-9 | Written |
Re-assessment
Re-assessment takes place when the summative assessment has not been completed by the original deadline, and the student has been allowed to refer or defer it to a later date (this only happens following certain criteria and is always subject to exam board approval). For obvious reasons, re-assessments cannot be the same as the original assessment and so these alternatives are set. In cases where the form of assessment is the same, the content will nevertheless be different.
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Problem sets | 1500 words on analysis of a problem set | 3-8, 9, 11 | August/September re-assessment period |
| Recorded presentation | 10 minute presentation on dataset for final paper | 3, 5, 6, 10 | August/September re-assessment period |
| Final paper | 1 written assignment with data analysis component (2000 words) | 1-11 | August/September re-assessment period |
