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 is currently a Ph.D. student in the Centre for Complex System Research, 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 current 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 researches 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

In this research, we aim to explore the patterns of inter-organizational response to disease outbreaks and develop social networks based measures for modelling and evaluating the coordination behaviour. We argue that coordination behaviour in a highly dynamic context such as responses disease outbreaks represent nonlinear patterns leading to emerging group behaviour. We further apply social networks based theory such as "Structural Holes" and "Strengths of Strong and Weak Tie" theory for explore the effectiveness and efficiency of optimized social network structures for improve response and intervention effort for disaster.

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.

Kwang Deok Kim

Exploring Emergency Response coordination through complex adaptive systems.

Traditional studies on coordination emphasised more stable and hierarchical environment and therefore is not suitable for explaining the coordination for dynamic and complex environment such as Emergency Response Coordination (ERC). In this study, we draw on coordination theory and network concepts to explore the problem of effective ERC. We argue ERC is dynamic and complex and therefore needs to have the characteristics of Complex Adaptive Systems (CAS) for it to be effective. We suggest the usefulness of social networks based approach to explore ERC problems and develop a social networks based coordination model for ERC in terms of complex networks.

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 the error rate. Conclusion can be drawn based on the trend after the warning. A decreasing trend would suggest that the behaviour was corrected and it was an unintentional error, otherwise fraud. Also if we look at the historical data before the marker we can make difference between steady error rate and increasing rate. An increasing rate without feedback could be explained by systematic misinterpretation or by testing the detection system and without alerts raised increasing abuse.

Alvaro Gonzalez

The improvement of design management in construction projects from the perspective of network analysis and as complex systems.

Of particular concern in the construction industry world-wide at present is design coordination and the high incidence (10%+ of contract sum) of construction rework attributable to design defects. network analysis may provide insight into how network structures employed in construction projects vary in their conduciveness to effective design coordination. This research aims to develop a comprehensive understanding of network behaviour and structure in construction, incorporating external factors such as project organisational design, space and logistical factors, internal factors such as individual actor attributes, through an integration application of social network analysis, coordination theory and construction specific procurement and management theory and any other relevant concepts which may offer opportunity for a conscious improvement of design management in the industry.

Jafar Hamra

Use of Social Network Analysis and coordination theory for Enhanced Bushfire Response Management.

The aim of my project is to address the emergency management interorganisational network in response to bushfire, specifically analysing the interactions among public, private, and nonprofits organizations evolving in response to the events of bushfire. During bushfire, the largest problems for bushfire managers often derive from collaborative problem solving and other problem of coordination between the different organisations. Social Network Analysis can assist bushfire managers in creating more effective network structure for their emergency management activities. Our research can be used to improve disaster response and improve the performance of response operations.

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. The 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.

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 thatsocial relationships and affiliation have powerful effects on physicaland mental health.But prevent obesity is not an easy challenge. A complex system orchestrates a 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 can contribute to research on the role of social environments in overweight and obesity and 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.

Tanvir Murshed

Studying communication network during organisational crisis.

The research is about studying communication network 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 the research in order to examine the crisis and subsequent disintegration of the network.

Mohammed Uddin

Modelling complex and dynamic coordination through social networks.

This PhD thesis concerns about the use of different methods of social network analysis (SNA) to analyze and model complex and dynamic coordination. The study of coordination draws upon a variety of different disciplines including computer science, network science, organization theory, management science, economic, and psychology. In this thesis, the main emphasis is given to the development of model for managing and organizing coordination both in intra- and inter-organization level. For this purpose, different methods of SNA and Network Science are used for analyzing and measuring coordination. Also, some statistical tools are used for testing proposed model with real life data.

The University of Sydney - Project Management