Big Data, gathered together and re-analysed, can be used to form endless variations of our persons - so-called ‘data doubles’. Whilst never a precise portrayal of who we are, they unarguably contain glimpses of details about us that, when deployed into various routines (such as management, policing and advertising) can affect us in many ways. How are we to deal with Big Data? When is it beneficial to us? When is it harmful? How might we regulate it? Offering careful and critical analyses, this timely volume aims to broaden well-informed, unprejudiced discourse, focusing on: the tenets of Big Data, the politics of governance and regulation; and Big Data practices, performance and resistance. An interdisciplinary volume, The Politics of Big Data will appeal to undergraduate and postgraduate students, as well as postdoctoral and senior researchers interested in fields such as Technology, Politics and Surveillance.

This book provides a comprehensive overview of how the course, content and outcome of policy making is affected by big data. It scrutinises the notion that big and open data makes policymaking a more rational process, in which policy makers are able to predict, assess and evaluate societal problems. It also examines how policy makers deal with big data, the problems and limitations they face, and how big data shapes policymaking on the ground. The book considers big data from various perspectives, not just the political, but also the technological, legal, institutional and ethical dimensions. The potential of big data use in the public sector is also assessed, as well as the risks and dangers this might pose. Through several extended case studies, it demonstrates the dynamics of big data and public policy. Offering a holistic approach to the study of big data, this book will appeal to students and scholars of public policy, public administration and data science, as well as those interested in governance and politics.

From one of the world’s leading data scientists, a landmark tour of the new science of idea flow, offering revolutionary insights into the mysteries of collective intelligence and social influence If the Big Data revolution has a presiding genius, it is MIT’s Alex “Sandy” Pentland. Over years of groundbreaking experiments, he has distilled remarkable discoveries significant enough to become the bedrock of a whole new scientific field: social physics. Humans have more in common with bees than we like to admit: We’re social creatures first and foremost. Our most important habits of action—and most basic notions of common sense—are wired into us through our coordination in social groups. Social physics is about idea flow, the way human social networks spread ideas and transform those ideas into behaviors. Thanks to the millions of digital bread crumbs people leave behind via smartphones, GPS devices, and the Internet, the amount of new information we have about human activity is truly profound. Until now, sociologists have depended on limited data sets and surveys that tell us how people say they think and behave, rather than what they actually do. As a result, we’ve been stuck with the same stale social structures—classes, markets—and a focus on individual actors, data snapshots, and steady states. Pentland shows that, in fact, humans respond much more powerfully to social incentives that involve rewarding others and strengthening the ties that bind than incentives that involve only their own economic self-interest. Pentland and his teams have found that they can study patterns of information exchange in a social network without any knowledge of the actual content of the information and predict with stunning accuracy how productive and effective that network is, whether it’s a business or an entire city. We can maximize a group’s collective intelligence to improve performance and use social incentives to create new organizations and guide them through disruptive change in a way that maximizes the good. At every level of interaction, from small groups to large cities, social networks can be tuned to increase exploration and engagement, thus vastly improving idea flow. Social Physics will change the way we think about how we learn and how our social groups work—and can be made to work better, at every level of society. Pentland leads readers to the edge of the most important revolution in the study of social behavior in a generation, an entirely new way to look at life itself.

In an era marked by unprecedented challenges, from the climate crisis to the rise of populism, the ways to manage public sector organisations have dramatically changed. In the eighth edition of this bestselling textbook, Flynn and Asquer offer the definitive introduction to public administration. Now substantially revised and updated throughout, this text reflects the latest approaches, tools and techniques that help governments respond to the multifaceted problems facing societies today and pre-empt those of tomorrow. Recognising the importance of context, Public Sector Managementunderscores that one-size-fits-all management practices are inadequate. Learn how public sector management adapts to changing political climates and societal pressures and be guided through the intricacies of making evidence-based policies while acknowledging the political dynamics that shape them. Updates to the eighth edition include: · A Global Perspective: Explore variations in public sector management shaped by cultural, historical, and institutional contexts, and gain a deep understanding of how governments address challenges in unique ways. · Balancing Theory and Practice: the new edition offers amore detailed and holistic perspective on public sector management by bringing in the latest theoretical insights and real-world public sector management practices. · Adapting to Change and tacking today’s issues: Confront the challenges faced in the age of technology, from artificial intelligence to Big Data; the climate crisis and clean energy transitions; and resulting from the latest geopolitical shifts including workforce migration to the erosion of trust in democracies. · A Call for Contextual Understanding: Learn how factors such as heterogeneity, population, income inequality, and technological access influence public sector management practices. Public Sector Management is essential reading for upper undergraduate and postgraduate students studying public sector management or public administration and is perfect for those studying on a Master of Public Administration programme. Norman Flynn was Director of the Centre for Financial and Management Studies, SOAS, University of London and Programme Director of the MSc in Public Policy and Management. Alberto Asquer is Head of the School of Finance and Management, Programme Director, MSc Public Policy and Management, and Senior Lecturer of Public Policy and Management at SOAS University of London

Big Data and Decision-Making: Applications and Uses in the Public and Private Sector breaks down the concept of big data to reveal how it has become integrated into the fabric of both public and private domains, as well as how its value can ultimately be exploited.

This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.

Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. - Learn general methods for specifying Big Data in a way that is understandable to humans and to computers - Avoid the pitfalls in Big Data design and analysis - Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources

This book offers an interdisciplinary analysis of current formations of publics that is informed by in-depth knowledge of affect and emotion theory. Using empirical case studies from contexts as diverse as India, Pakistan, Tanzania, and the Americas as well as Europe, the book challenges dichotomous distinctions between private and public. Instead, publics are understood as a relational structure that encompasses both people and their physical and mediatized environment. While each kind of public is affectively constituted, the intensity of its affective attunement varies considerably. The volume is aimed at academic readers interested in understanding the dynamic and fluid forms of contemporary formation of publics—be it digital or face-to-face encounters as well as in the intersection of both forms. This includes researchers from media and communication studies, social anthropology, theatre or literary studies. It is aimed at advanced students of these disciplines who are interested in the unfolding of contemporary publics.

This book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2020), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during 15–16 December 2020. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.

The ongoing growth of information and communication technology is a high priority for any developing country. These advances help progress with different sectors of socio-economic development within these countries, and strengthens our global economy as a whole. Securing Government Information and Data in Developing Countries provides an informative examination of the latest strategies and methods for protecting government information and data within developing countries. Presenting dynamic topics such as security-critical systems, watermarking authentication, hybrid biometrics, and e-voting systems, this publication is an ideal reference source for practitioners, academicians, students, and researchers who are interested in the emerging trends of data security for governments.