Current Research Projects

Arif Khan
Quantifying and Comparing the Dynamicity of Longitudinal Social Networks

Throughout our life, we participate in different social networks. Though in most cases we remain unaware of the big picture, our intuitive micro level interaction with others, ultimately defines the evolvement of these networks. Understanding these interactions can give insightful knowledge to a broad spectrum of disciplines. For example, it can help economists to predict how a particular market will grow or shrink in future and give necessary feedback into the system to avert any plunge. Or, for a biological perspective, it can help researchers to track certain virus spread and take countermeasures to quarantine people effectively. Thus, our research goal is to develop a framework that can give us these insights by exploring the dynamics of social networks. We follow topological approach which consists of several short interval network snapshots during overall time period and one aggregated network. Dynamic and static analysis methods are then applied on these two types of network consecutively. The results are compared to analyse dynamics of different longitudinal social networks. Also we formulated several temporal centrality based measures to find influential actors. Finally, this framework is applied on several real world datasets (e.g. bibliographic data on health science, organizational email dataset, incidence dataset etc.) to analyse their performance in terms of explaining underlying dynamics, top-ranked actors, future state etc.

Claire Kim
Effect of Feedback on Irregular Transactions

Claire’s research endeavors to understand coordination and performance within dynamic & distributed work groups and proposes a model using Self-Organization Theory (SOT) and an analytical perspective using social network analysis. This research intends to extend traditional coordination theory and its assumptions by studying how actors coordinate in a dynamic and distributed enrolment through varying social structure.

David Walker
Exploring the Role of Formal and Informal Network in Capacity Building Through Infrastructure Projects

This research aims to expand existing social network theories by applying them in the context of capacity building through infrastructure projects. Capacity building is an essential objective of interventions by government and non-government organisations in unstable and/or underdeveloped regions. This qualitative case-study research takes the relationship between a programme of development (the intervening actors) and a community (the target of capacity building efforts) as the unit of study. The research seeks to understand how different types of social networks affect capacity building outcomes. In particular the research focuses on the concept of power by exclusion, which predicts actors will be powerful in negotiations to the extent they are able to exclude the other actor from an exchange.

Dharshana Mahesh Kasthurirathna
Analysis on the Effect of Topology & Information Transfer on Network-based Games

Game theory tries to model the strategic decision making scenarios among individual players. In the real-world, the players who make strategic decisions are not isolated individuals but are members of populations that are connected according to a particular network topology. In this work, we try to analyse how network topology and the information transfer on top of the physical network, which affect the strategic decision making scenarios modelled in Game theory.

Muhammad Rabiul Hasan
Foodborne Disease Outbreak Coordination in Complex and Dynamic Multi-Organizational Networks

Rabiul’s PhD project focuses on potential development of a Hybrid Information Network (HIN) for Coordinating Foodborne Disease Outbreak in order to enhance early detection of an event, thus, would reduce the number of infected individuals and the overall impact on public health security. The research employs group of well-known theories such as coordination theory, game theory, network exchange theory, social exchange theory, centrality theory, and network tie theory as the basis of hybrid information network where emerging network structure at macro level and social media structure at micro level would potentially involve together in decision support systems in complex coordination environment, in this case for Foodborne Disease Outbreak. Rabiul has strong research interest in social media analytics for decision making, especially during crisis and emergency situation; and also organizational network analysis for improving coordination dilemma in complex inter-organizational settings.

Sanaz Khalili
Social Network Enabled Social Resilience€‹

The prime objective of this research is building and enhancing social resilience within communities in response to increasing climate-related disasters in the past couple of decades. With a growing population the world’s exposure to disasters is certainly increasing. In order to reduce social disaster losses in the future and to minimize any reduction in quality of life, this research focuses on identifying the most essential social resilience indicators within communities then exploring the impact of social network on social resilience and provides a novel and general framework for social resilience with the aim of enhancing resilient within communities.

Seyedamir Tavakoli Taba
Exploring the Ability to Improve Professional Performance Through Social Network Influence

It is believed that social relationships form a topology over which knowledge can flow. The nature of this research is to examine the effects of social network properties on knowledge transfer and expertise development among knowledge workers. Building on prior studies, this study views social network topology along structural, positional and relational dimensions. It is projected that this research develops a social network model of individual performance with the intention of understanding decision making, knowledge transfer and learning through the career. Furthermore, this work examines the influence of information and communication technologies (ICT) use and personal attributes on professional performance. As a case study, this research investigates the impact of radiologists’ social and professional network topologies on their reader performance.

Szabolcs Feczak
Social Network Analysis Mechanisms Embedded in the Collective Intelligence of Existing Communities of Practice

Our research aim is to advise a theoretical framework built on statistical and social network methods which increases the reliability and validity of labelling irregular transactions with tags: intentional (fraud) and unintentional (error). Using the point of time when a corrective feedback was sent and tracking the error rate in the claim category related, we can than analyse the effect of the feedback on an error rate. A Conclusion can be drawn based on a trend after the warning. A decreasing trend would suggest that the behaviour was corrected and was an unintentional error, otherwise fraud. An increasing rate without feedback could be explained by systematic misinterpretation or by testing the detection system and without alerts raised increasing abuse. When looking at the historical data before the marker, one can make-out a difference between steady error rate and increasing rate.

Upul Chathuranga Bandara Senanayake
Evaluating the Impact of a Scientist’s Research by using the Underlying Academic Network€‹

Upul's current research is on determining the quality of a researcher's research output. The popular system currently in use is the h-index which is the h number of papers that has at least h or more citations. However h-index has many drawbacks as pointed out by different scientists and it may encourage the creation of a huge body of academic papers which nobody reads, let alone utilizes, for further research or application. Upul has come up with a system to use the underlying complex network structure of the academic networks (citation networks and collaboration networks) that determines the quality of one's research in a fairer methodology and he has also found evidence to indicate his method is robust against manipulations and objective rather than been a subjective measure. Upul and his supervisor Dr. Piraveenan are currently applying the said evaluation system to real academic networks which is proving to be extremely interesting and fruitful.

Yamuna Subramaniyam
Trends of Network Properties in Confined Comminution

Yamuna’s research is about finding the trends of network properties in comminution using 3D Cellular Automata model. Flowing granular material exhibits complex behavior, including many phenomena that cannot be described in the context of a conventional fluid. For example, segregation, comminution and mixing all have no analogue in traditional fluids. To describe these phenomena the grain size distribution has to be involved as a dynamic property. Therefore, it is essential to mathematically model and analyze the real world systems. Also, it is vital to examine and categorize grains according to the size of the grain and finding the pattern of the result grain size distribution along with trends of the network properties like small-worldness and scale free.

Completed Research Projects

Alireza Abbasi
Evolution and Adaptation in Complex Networks

The real-world networks are usually very large, e.g., the Web hyperlink network (which consists of billion nodes and much more links). In addition it is difficult to extract such data. Therefore, to gain a deep understanding of the (real-world) network's structure, there is need for a mathematical theory or model to generate new networks that share certain properties of the network under examination. Then, we can understand the original network by building structures that resemble it.

To date, several models have been proposed to resemble the real-world networks. Barabasi-Albert (BA) Model is one of the most widely accepted models. They consider nodes' preferential attachment (the probability that a given node will receive a new link is proportional to the share of the total set of links that the node already owns) as a main factor of network evolution in addition to the growth of number of nodes and links. Therefore, the nodes' having higher number of links (degree centrality) can be regarded as the prominent nodes as they will gain more links in future during the evolution of the networks.

Analysing two real-world networks (collaboration networks) we found that while the number of links nodes have leads to gain more links in future but their brokering (bridging) role in the network, the extent to which a node brokers indirect connections between all other nodes in a network (betweenness centrality) have higher impact on gaining more new attachments during the evolution of the network.

Therefore, we propose a new model by replacing the probability of new attachments to a node from its degree centrality to betweenness centrality in BA model. So, our new model highlights a better factor on attracting new nodes during the evolution of a network.

If this principal governs in other networks (e.g., human social networks, inter-firm alliances (collaboration) networks, disease spreading networks), it could have marketing opportunities for marketing purpose (using human social networks, inter-firm alliances), research development (using scientific collaboration networks), health industry (using disease spreading networks) by investing more on the identified prominent nodes during the evolution of network.


Babak Amiri

An Efficient Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Networks

Babak Amiri completed his Phd in the Complex Systems Research Group, Faculty of Engineering and Information Technologies, The University of Sydney, Australia. Babak received his B.Sc. and M.Sc. degrees, in Industrial Engineering and Information Technology Engineering, respectively. His research interests are community detection in dynamic networks and network evolution. Community structure or clustering is one of the most relevant features of networks representing real systems. Community is a cluster of vertices in network, with many edges joining them and comparatively few edges joining vertices of different clusters. Community detection and network structure analysis recently have attracted the attention of researchers in deferent areas. This problem has been considered as an optimization problem and a new evolutionary optimization method will be introduced to solve it.


Fadl Bdeir

Modelling Inter-organisational Disease Outbreak Coordination

Investigating patterns of inter-organizational response to disease outbreaks and develop social networks based measures for modelling and evaluating the coordination behaviour. He argued that the coordination behaviour in a highly dynamic context such as the responses toward disease outbreaks, represent nonlinear patterns leading to emerging group behaviour. Applying further social networks based theories such as "Structural Holes" and "Strengths of Strong and Weak Tie" theory in order to explore the effectiveness and efficiency of optimized social network structures for improve response and intervention effort for disaster.

Georges Klopotowski
Network Structures, Family Ties and Childhood Obesity

The wide spread of overweight among children worldwide is growing at an alarming rate. Social relationships may contribute to the development of obesity through the interaction of biological, behavioural, and environmental factors. It is widely recognised that social relationships and affiliations have powerful effects on the physical and mental health, but the prevention of obesity is not an easy challenge. A complex system orchestrates the cascading causal process beginning with the macro-social to psychobiological processes that are dynamically linked together to form the processes by which social integration effects health.

In order to understand the influences network structure and function have on social and interpersonal behaviour it is necessary to operate at the behavioural and social levels. Social network approaches contribute to research in the role of social environments of the overweight and obese which strengthen interventions to prevent disease and promote health. By capitalising on the structure of the network system, a targeted intervention that uses social relationships in families, schools, neighbourhoods, and communities may be successful in encouraging healthful behaviours among children and their families.

Jafar Hamra
The Use of Social Network Analysis and Coordination Theory for Enhanced Bushfire Response Management

The aim of this Thesis was to address the emergency management interorganisational network in response to bushfires by specifically analysing the interactions among public, private, and nonprofits organizations evolving in response to the event of bushfires. During a bushfire the largest problems for bushfire managers often derive from collaborative problem solving and that of the coordination between different organisations. Social Network Analysis can assist bushfire managers in creating a more effective network structure for their emergency management activities. This research can be used to improve disaster response and improve the performance of response operations.

Kenneth Chung

Towards a Self-organization Coordination Performance Model for Dynamic & Distributed Work Groups

The performance of individuals in knowledge-intensive work and project environments is crucial to the success of the organisation at the macro-level. This research adopts a socio-technological approach in understanding the relationship between social networks (structure, position & ties), information and communication technology (ICT) use and individual performance by capitalising on theory from sociology (strength of ties & structural holes theory) and models of ICT use from Information systems (technology acceptance, social influence model). The results contribute to a larger understanding at the theoretical, methodological and domain level.

Dr Kenneth Chung is a lecturer in the Project Managment Program at the University of Sydney. For further information please follow this link:

Kwang Deok Kim
Exploring Emergency Response Coordination Through Complex Adaptive Systems

Kwang Deok Kim established a thesis that explores the viability of a policy network as a new approach for disaster management systems. Of primary interest is the relationship between the type of a policy network formed in the process of responding to an unexpected event and the type of a disaster management system. Relationships are investigated through an analysis of a qualitative case study from the various empirical sources such as media data and literatures to avoid a superficial understanding. This study argues that the policy network approach may be a promising countermeasure to a traditional approach, which provides substantial opportunity for the disaster management in a new light that provides an insight in establishing a more effective network for unexpected events in complex environments.

Mohammed Uddin
Modelling Complex and Dynamic Coordination Through Social Networks

This PhD thesis addresses the use of different methods in social network analysis (SNA) to analyze and model complex and dynamic coordination. Drawing upon a variety of different disciplines including computer science, network science, organization theory, management science, economic, and psychology. There is an emphasis given to the development model for managing and organizing coordination both in intra- and inter-organization levels. For this purpose, different methods of SNA and Network Science are used for analyzing and measuring coordination in conjunct with statistical tools which test proposed models with real life data.

Tanvir Murshed
The Study os Communication Networking During Organisational Crisis

Social network analysis tools and techniques are used in exploring the effects of crisis on the communication network structure. A Multilevel and Multitheoretical approach has been adopted in order to examine the crisis and subsequent disintegration of the communication network.