Why Change My Design: Explaining Poorly Constructed Visualization Designs with Explorable Explanations

Although visualization tools are widely available and accessible, not everyone knows the best practices and guidelines for creating accurate and honest visual representations of data. Numerous books and articles have been written to expose the misleading potential of poorly constructed charts and teach people how to avoid being deceived by them or making their own mistakes. These readings use various rhetorical devices to explain the concepts to their readers. In our analysis of a collection of books, online materials, and a design workshop, we identified six common explanation methods. To assess the effectiveness of these methods, we conducted two crowdsourced studies (each with N = 125) to evaluate their ability to teach and persuade people to make design changes. In addition to these existing methods, we brought in the idea of Explorable Explanations, which allows readers to experiment with different chart settings and observe how the changes are reflected in the visualization. While we did not find significant differences across explanation methods, the results of our experiments indicate that, following the exposure to the explanations, the participants showed improved proficiency in identifying deceptive charts and were more receptive to proposed alterations of the visualization design. We discovered that participants were willing to accept more than 60% of the proposed adjustments in the persuasiveness assessment. Nevertheless, we found no significant differences among different explanation methods in convincing participants to accept the modifications.Comment: To be presented at IEEE VIS 202

Does graphical reporting improve risk disclosure? Evidence from European banks

Purpose: This study examines the voluntary disclosure of risk-related issues, with a focus on credit risk, in graphical reporting for listed banks in the major European economies. It aims to understand if banks portray credit risk-related information in graphs accurately and whether these graphs provide incremental, rather than replicative, information. It also investigates whether credit risk-related graphs provide a fair representation of risk performance or a more favourable impression than is warranted. Design/Methodology/Approach: A graphical accuracy index was constructed. Incremental information was measured. A multi-level linear model investigated whether credit risk affects the quantity and quality of graphical credit risk disclosure. Findings: Banks used credit risk graphs to provide incremental information. They were also selective, with riskier banks less likely to use risk graphs. Banks were accurate in their graphical reporting, particularly those with high levels of credit risk. These findings can be explained within an impression management perspective taking into account human cognitive biases. Preparers of risk graphs seem to prefer selective omission over obfuscation via inaccuracy. This probably reflects the fact that individuals, and by implication annual report’s users, generally judge the provision of inaccurate information more harshly than the omission of unfavourable information. Research limitations/implications: This study provides theoretical insights by pointing out the limitations of a purely economics-based agency theory approach to impression management. Practical implications: The study suggests annual reports’ readers need to be careful about subtle forms of impression management, such as those exploiting their cognitive bias. Regulatory and professional bodies should develop guidelines to ensure neutral and comparable graphical disclosure. Originality/Value: This study provides a substantive alternative to the predominant economic perspective on impression management in corporate reporting, by incorporating a psychological perspective taking into account human cognitive biases

Interactive Data and Information Visualization: Unpacking its Characteristics and Influencing Aspects on Decision-making

Background: Interactive data and information visualization (IDIV) enhances information presentations by providing users with multiple visual representations, active controls, and analytics. Users have greater control over IDIV presentations than standard presentations and as such IDIV becomes a more popular and relevant means of supporting data analytics (DA), as well as augmenting human intellect. Thus, IDIV enables provision of information in a format better suited to users’ decision-making. Method: Synthesizing past literature, we unpack IDIV characteristics and their influence on decision-making. This study adopts a narrative review method. Our conceptualization of IDIV and the proposed decision-making model are derived from a substantial body of literature from within the information systems (IS) and psychology disciplines. Results: We propose an IS centered model of IDIV enhanced decision-making incorporating four bases of decision-making (i.e., predictors, moderators, mediators, and outcomes). IDIV is specifically characterized by rich features compared with standard information presentations, therefore, formulating the model is critical to understanding how IDIV affects decision processes, perceptual evaluations, and decision outcomes and quality. Conclusions: This decision-making model could provide a meaningful frame of reference for further IDIV research and greater specificity in IS theorizing. Overall, we contribute to the systematic description and explanation of IDIV and discuss a potential research agenda for future IDIV research into IS. Available at: https://aisel.aisnet.org/pajais/vol11/iss4/4

Does visualization matter? the role of interactive data visualization to make sense of information

As part of business analytics (BA) technologies, reporting and visualization play essential roles in mitigating users' limitations (i.e., being inexperienced, having limited knowledge, and relying on simplified information). Reporting and visualization can potentially enhance users' sense-making, thus permitting them to focus more on the information's message rather than numerical analysis. To better understand the role of reporting and visualization in a contextualized environment, we investigate using interactive data visualization (IDV) within accounting. We aim to understand whether IDV can help enhance non-professional investors' ability to make sense of foundational financial statement analyses. This study conducted an experiment using a sample of 324 nonprofessional investors. Our findings indicate that nonprofessional investors who use IDV are more heuristically adept than non-professional investors who use non-IDV. These findings enrich the theoretical understanding of business analytics' use in accounting decision making. The results of this study also suggest several practical courses of action, such as promoting wider use of IDV and making affordable IDV more broadly available, particularly for non-professional investors

Measuring and Disrupting Malware Distribution Networks: An Interdisciplinary Approach

Malware Delivery Networks (MDNs) are networks of webpages, servers, computers, and computer files that are used by cybercriminals to proliferate malicious software (or malware) onto victim machines. The business of malware delivery is a complex and multifaceted one that has become increasingly profitable over the last few years. Due to the ongoing arms race between cybercriminals and the security community, cybercriminals are constantly evolving and streamlining their techniques to beat security countermeasures and avoid disruption to their operations, such as by security researchers infiltrating their botnet operations, or law enforcement taking down their infrastructures and arresting those involved. So far, the research community has conducted insightful but isolated studies into the different facets of malicious file distribution. Hence, only a limited picture of the malicious file delivery ecosystem has been provided thus far, leaving many questions unanswered. Using a data-driven and interdisciplinary approach, the purpose of this research is twofold. One, to study and measure the malicious file delivery ecosystem, bringing prior research into context, and to understand precisely how these malware operations respond to security and law enforcement intervention. And two, taking into account the overlapping research efforts of the information security and crime science communities towards preventing cybercrime, this research aims to identify mitigation strategies and intervention points to disrupt this criminal economy more effectively

Mitigating Insider Threat using Human behavior Influence Models

Insider threat is rapidly becoming the largest information security problem that organizations face. With large numbers of personnel having access to internal systems, it is becoming increasingly difficult to protect organizations from malicious insiders. The typical methods of mitigating insider threat are simply not working, primarily because this threat is a people problem, and most mitigation strategies are geared towards profiling and anomaly detection, which are problematic at best. As a result, a new type of model is proposed in this thesis, one that incorporates risk management with human behavioral science. The new risk-based model focuses on observable influences that affect employees, and identifies employees with increased risk of becoming malicious insiders. The model\u27s primary purpose is to differentiate malicious and non-malicious employees. This research details the need for the model, the model\u27s components, and how it works. The model is tested using an in-depth case study on Robert Hanssen, the FBI\u27s double agent who sold the Soviets secrets for more than 20 years. Implemented with the right tool, the new model has great potential for use by security personnel in their efforts to mitigate insider threat damage

Big World, Small Planet – Module 4: Wants Versus Needs: Pushing the Boundaries, Teacher Edition

Big World, Small Planet – Module 4: Wants Versus Needs: Pushing the Boundaries, Teacher Edition We live in an interconnected world. Movies, music, news, manufactured goods like clothing and electronics, and people travel across the globe. With this much exchange of ideas, culture, and material goods, our actions in one region are sure to affect people living in other regions. Understanding how and where we connect can help us understand how we might impact others. This understanding can also help us find ways to make these new lines of contact work benefit of all