Data-driven modelling of social systems

Summary

The tools of physics will be applied to social dynamics data, to develop a predictive model, and ultimately inform policy decisions in the chosen area.

Supervisor(s)

Dr Tristram Alexander

Research Location

School of Physics

Program Type

Masters/PHD

Synopsis

The availability of immense quantities of data have made it possible to apply the techniques of physics to complex social problems, such as gun violence and political polarization. There are a wide range of possible research directions contained within this umbrella title, however all projects are united in the underlying methods being used. Data is used to develop a simplified model of the scenario in question, this simplified model is then used to make predictions, and these predictions are compared with the physical reality. A significant part of the project will be the development of suitable metrics to render the social phenomena of interest into a quantitative form. The specific tools of physics will then depend on the scenario. For gun violence for instance, agent-based modelling coupled with statistical mechanics and gun violence data can be used to explore different gun control measures, while political polarization can be explored using social media data, topic modelling and neural dynamics models. For more details on specific projects within this category, please contact the project supervisor.

Additional Information

The specific social problems of interest to the applicant will determine the co-supervisor and interaction opportunities. Possibilities include researchers in the School of Mathematics, the School of Linguistics, the School of Psychology, the United States Studies Centre and the Centre for Translational Data Science. 

HDR Inherent Requirements  

In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:   

  • Confidential disclosure and registration of a disability that may hinder your performance in your degree;
  • Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
  • Ability to perform independently and/or with minimal supervision;  
  • Ability to undertake certain physical tasks (e.g. heavy lifting);  
  • Ability to undertake observatory, sensory and communication tasks;  
  • Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);  
  • Ability to work in confined spaces or at heights;  
  • Ability to operate heavy machinery (e.g. farming equipment);  
  • Hold or acquire an Australian driver’s licence;  
  • Hold a current scuba diving license;  
  • Hold a current Working with Children Check;  
  • Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)  


You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

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Keywords

social dynamics, data science, agent-based models, statistical dynamics, computational physics, network analysis, Machine learning

Opportunity ID

The opportunity ID for this research opportunity is: 2694

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