IM903 Complexity in the Social Sciences
IM903
Complexity in the Social Sciences
Cross-Disciplinary Postgraduate Modules
IM901 Cultures of the Digital Economy
IM902 Appraoches to the Digital
IM904 Digital Objects, Digital Methods
IM913 Spatial Methods and Practice in Urban Science
IM914/QS906 Big Data Research: Hype or Revolution?
IM919 Urban Data - Theory and Methodology
IM922 Playful Media: Ludification in the Digital Age
IM923 User Interface Cultures: Design, Method and Critique
IM927 Digital Cities: Interdisciplinary Perspectives
IM928 Urban Resilience, Disasters and Data
IM929 Ethnography, Knowledge and Practice
IM931 Interdisciplinary Approaches to Machine Learning
IM934 Ecological Futures: Science, Culture and Media
QS903 Advanced Quantitative Research
15/20/30 CATS - (7.5/10/15 ECTS)
Easter Vacation
CIM and Centre for Complexity Science (CCS), Economics, Psychology, Statistics and Warwick Business School (WBS).
This module introduces an interdisciplinary group of students to some of the main quantitative and computational approaches for modelling complex social systems. You will be introduced to a range of methodological approaches from across a range of disciplines. You will be encouraged to think both practically and critically about some of the key issues raised by modelling complex social systems. You are expected to read core reading before each class, participate in group work and project presentations. No prerequisites are required for this module. However, please note that some of this teaching will involve mathematics and related computational techniques. You will all work in ‘teams’ or ‘pairs’ allowing a range of disciplinary backgrounds to come together and work on similar problems. A key part of this module is to learn to work with others in different disciplines. In addition, the assessment is designed to support both those with more mathematical background as well as those with little or no mathematical background.
Module Convenors - Dr Emma Uprichard, CIM / Dr Colm Connaughton, Maths
Indicative Syllabus
Please note that the exact content may vary due to staff availability.
Day 1 |
AM - Introduction to Module |
PM - Networks / Complex Policy and Evaluation |
|
Day 2 |
AM - Food security and a quantitative approach to policy design |
PM - Using language networks to understand the mind |
|
Day 3 |
AM - Understanding and using social network data |
PM - Computational social science and big data |
|
Day 4 |
AM - Game theory across the disciplines |
PM - "The plural of 'traders' is not 'market" |
|
Day 5 |
AM - Simulating the Social |
PM - Assessment Workshop |
Illustrative Bibliography
Ball, P. (2012) 'Why Society is a complex matter', Springer.
Barabási, A.-L., "Scale-Free Networks". Scientific American 288,60 (May 2003).
Caldarelli, D (2007) Scale-Free Networks: Complex Webs in Nature and Technology, Oxford Finance Series.
Holland, J. (1999) Emergence from Chaos to Order. Mass: Perseus Press.
Johnson, S. (2001) Emergence: The Connected Lives of Ants, Brains, Cities and Software. New York: Scribner.
Kauffman, S. (1995) At Home in the Universe. London: Viking.
Room, G. (2011) Complexity, Institutions and Public Policy: Agile Decision-making in a Turbulent World, Cheltenham: Edward Elgar.
Sawyer, K. (2003) Social Emergence: Societies as Complex Systems, Cambridge: Cambridge University Press
Waldrop, M. (1992) Complexity: The Emerging Science at the Edge of Order and Chaos. New York: Simon and Schuster
Jensen, HJ (1998) Self-Organized Criticality. Cambridge: CUP
Strogatz, S.H. (2000) Nonlinear dynamics and chaos. (Westview Press).
Learning Outcomes
By the end of the module, students should be able to:
- develop independent critical thinking;
- appreciate multi-disciplinary approaches to complex systems;
- work in a team where others have more or less technical, mathematical, or computational expertise for problems arising at the forefront of Complexity Science;
- work in teams; and
- communicate with their peers and with other academics within and outside of one’s own discipline.
Important Registration Information:
CIM Students
- Please first discuss your optional module choices with you personal tutor during the personal tutor meetings and get their approval
- Then complete and submit the optional module choice webform available in the CIM welcome page
- The webform opens on Wednesday 29th September at 14:00 BST and closes on Thursday 30th September at 15:00 BST
- If there are any queries, please get in touch with Clare (PG Coordinator) via cim@warwick.ac.uk
External Students
- All external students - Please contact the CIM PG Coordinator (Clare) via email (cim@warwick.ac.uk), to request your optional module choice by Week 1: Wednesday 6th October at 17:00 BST.
PLEASE NOTE
- Please be advised that you may be expected to have access to a laptop for some of these courses due to software requirements; the Centre is unable to provide a laptop for external students.
- Please be advised that some modules may have restricted numbers and places are allocated according to availability.
- Please note that a request does NOT guarantee a place on the module and is subject to availability.
- Gaining permission of a member of CIM teaching staff or a member of staff from your home department or filling in the eVision Module Registration (eMR) system with the desired module does NOT guarantee a place on that module.
- Requests after the specified deadline will not be considered.
- The CIM PG Coordinator will get back confirming your place in the module by Friday 1st October (For CIM students).
- For external students - Only after confirmation of a place from CIM PG Coordinator can students’ or their home departments confirm their registration on eVision/MRM. Registrations by students who have not received confirmation of a place from CIM will be rejected via the system.
NOTE – The above-mentioned registration deadline also applies to the CIM optional modules running in Term 2. We will consider registrations again in the first week of Term 2, but only in relation to modules where there is availability.
We are normally unable to allow students (registered or auditing) to join/leave the module after the second week of it commencing.