Research students

Szabolcs Feczak
Effect of feedback on irregular transactions
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.

Georges Klopotowski
Social network analysis mechanisms embedded in the collective intelligence of existing communities of practice.
Health Online Communities help maximize relationships among stakeholders of the Health Care sector increasing participation and leading to positive health behavior changes. The study of different types of Social Network structures and their implications on online CoPs analyzes traffic patterns through specialized Social Network Analysis Algorithms in order to provide to Health Care Insurers fast and reliable sets of decision-making information to improve their Disease Management Cycle.

Kenneth Chung - Awarded PhD Dec 08
Understanding knowledge-intensive work performance:The influence of social networks and ICT use.
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.

Claire Kim
Towards a self-organization coordination performance model for dynamic & distributed work groups.
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.

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

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.

Nathan McKinlay
Rule based collective intelligence networks for health insurance fraud.
Analysing Health Insurance processes, measuring these against expected and actual behaviour combined with work flow modelling and collective intelligence systems will allow for an improved understanding of Health Insurance processes, while at the same time allowing for the development of incident dashboards .

The Heath Insurance industry is driven by process based rules. It is through rules the Insurance company pays on claims or investigates the claim for potential errors or fraud.
This research aims to connect into the HI-SONAR project.

SK Chong
Towards a network based Coordination in complex construction project
The primary objective of each project team is to complete the project within the time frame and budget, safely. For success, it calls for skilful management of change in order that adverse factors to deviate from the planned, be contained.

This research adopts an overview in understanding the relationship of the team’s social networks (structure, position & ties), information and communication flow as how they would adapt itself to self organizing fundamental to mitigate issues of complex situation, to meet deadline by sub teams within the project organization.

Sumit Gupta

Detection of Insider Trading using Social Network Analysis (SNA)

Insider trading is an increasing problem in today's finance markets which threatens the interest and trust of other investors and thus further results in capital misallocation and inefficiencies. The insiders work alone and/or in groups and are able to adapt to the changing laws and the technology. In our research, we are proposing the use of Social Network Analysis (SNA) for detection of the insiders. SNA with combination of other tools like data mining, pattern recognition and self-learning algorithms can help us in detecting illegal individual and group insiders’ activity.