University College London Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
Norwich Research Park Featured PhD Programmes
Imperial College London Featured PhD Programmes
University of Reading Featured PhD Programmes

Evolution and Dynamics of Complex Social Networks

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

**THIS OPPORTUNITY IS FOR AUSTRALIAN DOMESTIC CANDIDATES ONLY**

The Project

The main goal of the PhD project is to build robust models of Complex Social Networks (CSNs) taking simultaneously into account their structure, dynamics and control (for details please see below).

There is a great interest in controlling of complex networks, including Complex Social Networks (CSNs), as this has great potential to make a big impact on tackling important societal challenges. There have been attempts to use control theory to approach this research challenge, however, due to the heterogeneous nature of social networks and their non-linear character, neither the network model nor the dynamics can be analytically described. This poses severe constraints on controllability of CSNs. To address these issues, there is an urgent need for extensive research into the CSNs’ controllability and suitable control mechanisms that would enable to direct the evolution of such networks in a desired way.

The fundamental research in the area of controlling complex networks, which is the main focus of this project, has a wide range of applications, one of them being changing human behaviour. Gender imbalance, minority marginalisation, and organised criminal behaviour, which are the main case studies to be developed within this project, represent only few challenges that modern society faces.
It is now for the first time in the human history, that we have the possibility to process big social data about the variety of interactions and activities of millions of individuals that can be represented as a CSN. It represents an increasingly important resource in the process of understanding behaviour of individuals, groups and whole communities yet there is no coherent and comprehensive approach (i) to analyse and model complex social networks, (ii) together with their non-linear dynamics and (iii) evolution, both triggered by natural dynamic processes occurring in such networks and the control mechanisms introduced to the network. All three components are crucial to advance our understanding of continuously changing people’s behaviour and propose mechanisms that help to change this behaviour if desired or necessary.

Networked systems and their evolution are usually analysed by building models of interactions including random, scale-free, and small-world models. However, these do not reflect the complex nature of real-world CSNs and related processes with high enough accuracy for their effective control. Building on the previous related research the proposed transformative route forward to overcome the limitations of existing techniques for CSNs control is, therefore, in developing novel high accuracy data-driven social network simulation models with ability to accurately model and take into account the inherent CSN dynamics as well as the dynamic behaviour induced by the applied, proposed control mechanisms.

Thus, the main goal is to build a robust and adaptive framework (DynaCo) that will address the following objectives:
● Objective 1 (OB1): To build robust models of Complex Social Networks (CSNs) taking simultaneously into account their structure, dynamics and control;
● Objective 2 (OB2): To develop methods for assessing a level of the CSN controllability;
● Objective 3 (OB3): To develop control mechanisms and analyse how they influence a CSN’s characteristics, structure, and dynamics;
● Objective 4 (OB4): To apply outcomes of OB1-OB3 in the context of three case studies (gender imbalance, minority marginalisation, and organised criminal behaviour).

This PhD project is mainly associated with OB1 of this Dynamics and Control of Complex Social Networks project (ARC DP190101087).

About the Faculty

The Faculty of Engineering and Information Technology at UTS is a world-class faculty with a growing reputation for its quality and impact. Our research is highly advanced, industry-focused and part of the lively and rigorous research culture at UTS.

Focused on ’practical innovation’, our researchers are pioneering research solutions with real-world impact. They’re recognised leaders in their fields, responsible for delivering new, better and more cost-effective innovative solutions to current national and international challenges.

About the University

UTS is a dynamic and innovative university in central Sydney. One of Australia’s leading universities of technology, UTS has a distinct model of learning, strong research performance and a leading reputation for engagement with industry and the professions.

UTS has a culturally diverse campus life and vibrant international exchange study and research programs that prepare graduates for the workplaces of today and the future.

We also maintain strong relationships with the local community, industry, business and the professions through a wide range of partnerships, projects and events.

https://www.uts.edu.au/

https://www.uts.edu.au/about/faculty-engineering-and-information-technology

https://www.uts.edu.au/staff/katarzyna.musial-gabrys

Funding Notes

Scholarships available
Scholarships are tax-free and valued at $27,082 pa (indexed annually) for 3 years.

Top-up scholarships, up to a maximum value of $12,000pa (for 3 years), may also be allocated to exceptional domestic candidates awarded competitive scholarships.

Application Deadlines -Australian Domestic Students
Spring 2019 - 30 April 2019 - For commencement July 2019
Autumn 2020 - 30 September 2019 - For commencement January 2020

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.