Improving information requirements determination: a cognitive perspective

The novel coronavirus (COVID-19) pandemic spread globally from its outbreak in China in early 2020, negatively affecting economies and industries on a global scale. In line with historic crises and shock events including the 2002-04 SARS outbreak, the 2011 Christchurch earthquake and 2017 Hurricane Irma, COVID-19 has significantly impacted global economic conditions, causing significant economic downturns, company and industry failures, and increased unemployment. To understand how conditions created by the pandemic to date compare to the aforementioned shock events, we conducted a thorough literature review focusing on the presentation of panic buying and herd mentality behaviours, changes to discretionary consumer spending as defined by Maslow’s Hierarchy of Needs, and the impact of global media on these behaviours. The methodology utilised to analyse panic buying, herd mentality and altered patterns of consumer discretionary spending (according to Maslow’s theory) involved an analysis of consumer spending data, largely focused on Australian and American markets. Here, we analysed the volume and timing of consumer spending patterns; the volumes of spending on specific, highly-demanded consumer goods during the investigative period; and the distribution of spending on luxury and non-durable goods to identify the occurrence of these consumer behaviours. Moreover, to identify the presence of the media in influencing consumer behaviour we focused on web traffic to media sites, alongside keyword and phrase data mining. We conclude that, to date, consumer behaviour during the COVID-19 crisis appears to align with behaviours exhibited during historic shock events. We hope to contribute to the body of research on the early months of this pandemic before longer-term studies are available.

https://www.econstor.eu/bitstream/10419/239265/1/1742496768.pdf

Consumer behaviour during crises: Preliminary research on how coronavirus has manifested consumer panic buying, herd mentality, changing discretionary spending and the role of the media in influencing behaviour

The increasing interest in time series data mining in the last decade has resulted in the introduction of a variety of similarity measures, representations, and algorithms. Surprisingly, this massive research effort has had little impact on real world applications. Real world practitioners who work with time series on a daily basis rarely take advantage of the wealth of tools that the data mining community has made available. In this work, we attempt to address this problem by introducing a simple parameter-light tool that allows users to efficiently navigate through large collections of time series. Our system has the unique advantage that it can be embedded directly into any standard graphical user interfaces, such as Microsoft Windows, thus making deployment easier. Our approach extracts features from a time series of arbitrary length and uses information about the relative frequency of its features to color a bitmap in a principled way. By visualizing the similarities and differences within a collection of bitmaps, a user can quickly discover clusters, anomalies, and other regularities within their data collection. We demonstrate the utility of our approach with a set of comprehensive experiments on real datasets from a variety of domains.

/pdf/time-series-bitmaps-a-practical-visualization-tool-for-51lh6uk2it.pdf

Time-series Bitmaps: a Practical Visualization Tool for Working with Large Time Series Databases.

The contribution of horizontal gene transfer (HGT) to the evolution of Mycobacterium tuberculosis -- the main causal agent of tuberculosis in humans -- and closely related members of the M. tuberculosis complex remains poorly understood. Using a combination of genome-wide parametric analyses, we have identified 48 M. tuberculosis chromosomal regions with atypical characteristics, potentially due to HGT. These specific regions account for 4.5% of the genome (199 kb) and include 256 genes. Many display features typical of the genomic islands found in other bacteria, including residual material from mobile genetic elements, flanking direct repeats, insertion in the vicinity of tRNA sequences, and genes with putative or documented virulence functions. Southern blotting analysis of nine of these 48 regions confirmed their presence in "Mycobacterium prototuberculosis," the ancestral species of the M. tuberculosis complex. Finally, our results strongly suggest that the ancestor of the tubercle bacilli was an environmental bacillus that exchanged genetic material with other bacterial species, including Proteobacteria in particular, present in its surroundings. This study describes a rational approach to searching for mycobacterial virulence genes, and highlights the importance of dissecting gene transfer networks to improve our understanding of mycobacterial pathogenicity and evolution.

/pdf/contribution-of-horizontally-acquired-genomic-islands-to-the-3gnv87ui3z.pdf

Contribution of Horizontally Acquired Genomic Islands to the Evolution of the Tubercle Bacilli

Recent advancements in sensor technology have made it possible to collect enormous amounts of data in real time. However, because of the sheer volume of data most of it will never be inspected by an algorithm, much less a human being. One way to mitigate this problem is to perform some type of anomaly (novelty /interestingness/surprisingness) detection and flag unusual patterns for further inspection by humans or more CPU intensive algorithms. Most current solutions are “custom made” for particular domains, such as ECG monitoring, valve pressure monitoring, etc. This customization requires extensive effort by domain expert. Furthermore, hand-crafted systems tend to be very brittle to concept drift. In this demonstration, we will show an online anomaly detection system that does not need to be customized for individual domains, yet performs with exceptionally high precision/recall. The system is based on the recently introduced idea of time series bitmaps. To demonstrate the universality of our system, we will allow testing on independently annotated datasets from domains as diverse as ECGs, Space Shuttle telemetry monitoring, video surveillance, and respiratory data. In addition, we invite attendees to test our system with any dataset available on the web.

/pdf/assumption-free-anomaly-detection-in-time-series-a2imof7ire.pdf

Assumption-free anomaly detection in time series

Chaos game visualization of sequences

Chaos and graphicsChaos game visualization of sequences

Relationship definition and management: tools for requirements analysis

A new conceptual and formal framework for analyzing economic decisions, the homo communitatis paradigm, is introduced. The framework is in the form of seven principles, which collectively articulate the entire range of factors that affect choice, including all aspects of individual behavior and of the social context—the communities—the actor is a member of. Traditional economic analysis is shown to be a special case of homo communitatis analysis in which key variables are omitted. Using the principles, we show that experimental results such as loss aversion, framing effects, mental accounting, and judgment biases are not irrational and that the apparent irrationality is in every case an illusion arising from incomplete specification and control of independent variables elucidated in the principles. Several implications for future work are discussed, including high-fidelity models of socioeconomic systems, significantly more powerful and detailed economics simulations, and adoption of significantly differe...

The Irrationality Illusion: A New Paradigm for Economics and Behavioral Economics

Economic simulations typically focus almost exclusively on economic variables. If non-economic factors are included at all, it is usually in some form of utility function calculation. This paper presents a model that allows formal specification of a much broader range of factors, processes, and quantities involved in human communities—families, businesses, ethnic groups, nations, work teams, cultures. The phenomena include the hierarchically structured social practices of the group, the principles that underlie choices in the community, and the recognizable positions or statuses in the community. This allows us to model intrinsic or expressive behavior, capturing the concept of multi-aspect identity and the impact of the principles of the group on individual behaviors, all in formal and quantitative form. Having these factors represented formally enables the creation of significantly more realistic simulations incorporating a much wider range of variables, particularly when the economic facts and quantiti...

H. Joel Jeffrey

Papers

Chaos game visualization of sequences

Chaos and graphicsChaos game visualization of sequences

Relationship definition and management: tools for requirements analysis

The Irrationality Illusion: A New Paradigm for Economics and Behavioral Economics

Expanding the Range of Behavioral Factors in Economic Simulations