Visibility Threshold: Some Considerations on Data Mining Applied to the Study of Eblaite Society

Accounting is a routine activity. Through repetition, the scribes of the Ebla Archives (Syria, 24th cent. BCE) have been able to record thousands of transactions. They organized and stored accounting data referred to more than thirty years of the Palace G activities. The recurring textual patterns characterizing the administrative corpus are a byproduct of this routine-based approach. The ability to see recurring patterns in the textual record is fundamental when dealing with an administrative corpus: however, this ability fails when the patterns are buried in data. In this paper, I argue that theoretical aspects of data mining are not far from theoretical and methodological tenets of the historical approach. Data mining is a useful technique for the identification of document clusters and relevant information which would otherwise remain hidden. Furthermore, textual pattern recognition is critical to address topics such as the study of society: belonging to a category of complex problems, any socio-historical investigation requires dealing with multiple interconnected variables. However, not all research topics require such an approach. I define the line beyond which digital approaches are extremely useful (if not indispensable) as 'visibility threshold’. The position of this interface is relative and subjective.

When community change theory meets practice: Exploring some of the challenges to information sharing networks for community change

Networked community change (NCC) efforts focus on building and supporting networks of stakeholders in communities to address complex problems, with a particular focus on tie formation among stakeholders and organizer facilitation of an information-sharing network (Lawlor & Neal, 2016). NCC approaches include, for example, systemic action research (Burns, 2007), Collective Impact (Kania & Kramer, 2011), and network action research (Foth, 2006) and can be understood as community-level interventions supporting change (Bess, 2015). Previous research demonstrates the promising nature of NCC efforts under ideal circumstances for efficient information sharing in community change efforts. However, these efforts frequently operate in non-ideal conditions, needing to adapt to a variety of community challenges. This article extends the agent-based simulation model presented in Lawlor and Neal (2016) to reflect the challenges that arise when stakeholders implement these approaches to community change and identify how they can impact information-sharing networks. First, we review literature to establish common challenges that arise in these efforts. Second, we employ the Lawlor and Neal (2016) model to examine these challenges and report on the resulting structure of the information-sharing networks that emerge from implementing them in the simulation model. We conclude with implications of common networked community change challenges on network formation and future directions for addressing these real-world challenges as communities work on complex problems.

Critical Thinking and the Socratic Method

This chapter starts by answering the question, “What is critical thinking?” As it turns out, not everyone agrees on what critical thinking is. Nevertheless, researchers agree that critical thinking allows many people to reason together for solutions to complex problems. Also, in this chapter, the authors look at how computing capabilities enhance Socratic problem solving. A computer-based Socratic problem-solving system can keep problem solvers on track, document the outcome of a problem-solving session, and share those results with participants and a larger audience. In addition, Socrates DigitalTM can also help problem solvers combine evidence about their quality of reasoning for individual problem-solving steps and the overall confidence level for the solution.

Social Pathologies

Social pathologies have been recognised to be very complex problems as they affect the individual's psychology as well as his/her body. As a result, they have been approached from a normativist way as well as a naturist way by considering society as an organic or normative entity. There is no consensus whether social pathologies are the result of social ills that affect the individual or the reverse. Whichever way one approaches them, they are there, and a social pedagogue is the key to alleviating or minimising the impact of such pathologies on the individual and society at large. His/her role in making such valuable contribution can not be disputed. Due to a great number of factors that give rise to such pathologies as they are context and content dependent, one size does not fit all. It is the social pedagogue that has to act in a prognostic, diagnostic, and therapeutic way and thus his/her role needs to be clearly defined.

Deep Reinforcement Learning for Cybersecurity Applications

There has been a rapid growth of the devices connected to the internet in the last decade for the various internet (IoT) of things applications. The increase of these smart devices has posed a great security concern in the internet of things ecosystem. The internet of things ecosystem must be protected from these threats. Reinforcement learning has been proposed by the cybersecurity professionals to provide the needed security tools for securing the IoT system since it is able to interact with the environment and learn how to detect the threats. This paper presents a comprehensive research on cybersecurity threats to the IoT system applications. The RL algorithms are also presented to understand the attacks on the IoT. Reinforcement learning is widely employed in cybersecurity because it can learn on its own experience by investigating and capitalizing on the unknown ecosystem, this enables it solve many complex problems. The RL capabilities on dealing with cybercrime challenges are also exploited in this paper.

Systematically Understanding Cybersecurity Economics: A Survey

Insights in the field of cybersecurity economics empower decision makers to make informed decisions that improve their evaluation and management of situations that may lead to catastrophic consequences and threaten the sustainability of digital ecosystems. By drawing on these insights, cybersecurity practitioners have been able to respond to many complex problems that have emerged within the context of cybersecurity over the last two decades. The academic field of cybersecurity economics is highly interdisciplinary since it combines core findings and tools from disciplines such as sociology, psychology, law, political science, and computer science. This study aims to develop an extensive and consistent survey based on a literature review and publicly available reports. This review contributes by aggregating the available knowledge from 28 studies, out of a collection of 628 scholarly articles, to answer five specific research questions. The focus is how identified topics have been conceptualized and studied variously. This review shows that most of the cybersecurity economics models are transitioning from unrealistic, unverifiable, or highly simplified fundamental premises toward dynamic, stochastic, and generalizable models.