Changing the company name : a model for identity change through communication

In an ever evolving business landscape, change is an ever present part of any organisation’s lifecycle. This thesis presents communication as a fundamental element of effective change management. Drawing from the existing change communication literature and two case studies, this thesis examines how organisations utilise strategic change communication to manage identity change. As a result this study presents a conceptual model that outlines a process of change communication strategy and implementation. This model is offered as a step toward connecting important scholarship into a more comprehensive portrait of change communication during identity change than so far has been available.

Collaboration in Web N.0: Stigmergy and virtual pheromones

The aim of this project was to develop a general theory of stigmergy and a software design pattern to build collaborative websites. Stigmergy is a biological term used when describing some insect swarm-behaviour where 'food gathering' and 'nest building' activities demonstrate the emergence of self-organised societies achieved without an apparent management structure. The results of the project are an abstract model of stigmergy and a software design pattern for building Web 2.0 components exploiting this self-organizing phenomenon. A proof-of-concept implementation was also created demonstrating potential commercial viability for future website projects.

Self and other in communication and cognition : the role of auto-communication and intersubjectivity in autopoiesis of psychic systems

By referring to Niklas Luhmann's theory of self-referential systems, Aldo Mascareño (2008, submitted for publication) gives an account of system-environment interrelatedness, explaining how social and individual constitute each other through the process of communication and co-creation of meanings. Two possible extensions to his account are discussed. Firstly, auto-communication within the system that happens without any external reference needs to be taken into account while describing the existence and constant re-creation of psychic systems. Secondly, in order for the system and environment or two systems to communicate, an imagined and temporary intersubjectivity between the two needs to be assumed.

Topical pattern based document modelling and relevance ranking

For traditional information filtering (IF) models, it is often assumed that the documents in one collection are only related to one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling was proposed to generate statistical models to represent multiple topics in a collection of documents, but in a topic model, topics are represented by distributions over words which are limited to distinctively represent the semantics of topics. Patterns are always thought to be more discriminative than single terms and are able to reveal the inner relations between words. This paper proposes a novel information filtering model, Significant matched Pattern-based Topic Model (SPBTM). The SPBTM represents user information needs in terms of multiple topics and each topic is represented by patterns. More importantly, the patterns are organized into groups based on their statistical and taxonomic features, from which the more representative patterns, called Significant Matched Patterns, can be identified and used to estimate the document relevance. Experiments on benchmark data sets demonstrate that the SPBTM significantly outperforms the state-of-the-art models.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Decentralised Communication in Autonomous Agent Swarms

Communication and information diffusion are typically difficult in situations where centralised structures may become unavailable. In this context, decentralised communication based on epidemic broadcast becomes essential. It can be seen as an opportunity-based flooding for message broadcasting within a swarm of autonomous agents, where each entity tries to share the information it possesses with its neighbours. As an example of applications for such a system, we present simulation results where agents have to coordinate to map an unknown area.

Communication and essentialism: Grounding the shared reality of a social category

Essentialism is an ontological belief that there exists an underlying essence to a category. This article advances and tests in three studies the hypothesis that communication about a social category, and expected or actual mutual validation, promotes essentialism about a social category. In Study 1, people who wrote communications about a social category to their ingroup audiences essentialized it more strongly than those who simply memorized about it. In Study 2, communicators whose messages about a novel social category were more elaborately discussed with a confederate showed a stronger tendency to essentialize it. In Study 3, communicators who elaborately talked about a social category with a naive conversant also essentialized the social category. A meta-analysis of the results supported the hypothesis that communication promotes essentialism. Although essentialism has been discussed primarily in perceptual and cognitive domains, the role of social processes as its antecedent deserves greater attention.

Enterprise-related crisis communication on Twitter

The rise of social media as communication channels has enabled customers to provide feedback or to ask for assistance quickly and easily. In the context of brand crises, the microblogging platform Twitter is highly relevant because of its ability to support information sharing. By investigating communication on Twitter, the authors examine Twitter activity patterns based on a dataset of some 240,000 tweets during two major brand crises affecting the Australian airline Qantas – the volcanic ash cloud caused by the eruption of Chilean volcano Puyehue in June 2011, and the global grounding of Qantas flights by management in the course of an industrial dispute in October/November 2011. Through this case study we find that characteristics of communication change significantly during different stages of the crisis. Further, we demonstrate that different kinds of crisis result in different communication patterns on Twitter.

Exploring factors influencing adherence to lifestyle modifications in Chinese people with hypertension: The role of concordance during health communication

This study investigated the factors influencing the conduct of modifying unhealthy lifestyles in Chinese people with high blood pressure, and examined the effect of health communication between health professionals and patients on their health behaviours. The thesis proposes a new theoretical framework to explain and predict individuals' behaviours which can be used to design interventions to improve their health behaviours.

Pattern-based topic modelling and its application for information filtering and information retrieval

This thesis targets on a challenging issue that is to enhance users' experience over massive and overloaded web information. The novel pattern-based topic model proposed in this thesis can generate high-quality multi-topic user interest models technically by incorporating statistical topic modelling and pattern mining. We have successfully applied the pattern-based topic model to both fields of information filtering and information retrieval. The success of the proposed model in finding the most relevant information to users mainly comes from its precisely semantic representations to represent documents and also accurate classification of the topics at both document level and collection level.

Reliable, cloud-based communication for multi-robot systems

In contrast to single robotic agent, multi-robot systems are highly dependent on reliable communication. Robots have to synchronize tasks or to share poses and sensor readings with other agents, especially for co-operative mapping task where local sensor readings are incorporated into a global map. The drawback of existing communication frameworks is that most are based on a central component which has to be constantly within reach. Additionally, they do not prevent data loss between robots if a failure occurs in the communication link. During a distributed mapping task, loss of data is critical because it will corrupt the global map. In this work, we propose a cloud-based publish/subscribe mechanism which enables reliable communication between agents during a cooperative mission using the Data Distribution Service (DDS) as a transport layer. The usability of our approach is verified by several experiments taking into account complete temporary communication loss.

Effective communication during disasters: What effects community decision making & action?

Study/Objective This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. Background In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. Methods To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Results Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. Conclusion The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.

Effective communication during disasters

This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.