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What is complexity? What are the characteristics of a complex system? What does it mean to measure? How to develop an efficient tool for measuring socio-economic phenomena? What is synthesis? What are the main statistical tools for synthesis of multi-indicator systems? These are the research questions that are attempted to be answered in this book, the result of the author’s research work during his PhD. The book offers a conceptual and methodological analysis of the topic of synthesis of complex social phenomena, also proposing interesting applications to real cases. Winner of the Competition “Prize for PhD Thesis 2020” arranged by Sapienza University Press.
This text is about spreading of information and influence in complex networks. Although previously considered similar and modeled in parallel approaches, there is now experimental evidence that epidemic and social spreading work in subtly different ways. While previously explored through modeling, there is currently an explosion of work on revealing the mechanisms underlying complex contagion based on big data and data-driven approaches. This volume consists of four parts. Part 1 is an Introduction, providing an accessible summary of the state of the art. Part 2 provides an overview of the central theoretical developments in the field. Part 3 describes the empirical work on observing spreading processes in real-world networks. Finally, Part 4 goes into detail with recent and exciting new developments: dedicated studies designed to measure specific aspects of the spreading processes, often using randomized control trials to isolate the network effect from confounders, such as homophily. Each contribution is authored by leading experts in the field. This volume, though based on technical selections of the most important results on complex spreading, remains quite accessible to the newly interested. The main benefit to the reader is that the topics are carefully structured to take the novice to the level of expert on the topic of social spreading processes. This book will be of great importance to a wide field: from researchers in physics, computer science, and sociology to professionals in public policy and public health.
Complexity systems are at the heart of behavior
This book argues that societies are complex dynamical systems that can be understood through the concept of emergence.
This book explores the view that normative behaviour is part of a complex of social mechanisms, processes and narratives that are constantly shifting. From this perspective, norms are not a kind of self-contained social object or fact, but rather an interplay of many things that we label as norms when we ‘take a snapshot’ of them at a particular instant. Further, this book pursues the hypothesis that considering the dynamic aspects of these phenomena sheds new light on them. The sort of issues that this perspective opens to exploration include: Of what is this complex we call a "social norm" composed of? How do new social norms emerge and what kind of circumstances might facilitate such an appearance? How context-specific are the norms and patterns of normative behaviour that arise? How do the cognitive and the social aspects of norms interact over time? How do expectations, beliefs and individual rationality interact with social norm complexes to effect behaviour? How does our social embeddedness relate to social constraint upon behaviour? How might the socio-cognitive complexes that we call norms be usefully researched?
This book studies social phenomena in a new way, by making judicious use of computer technology. The book addresses the entire spectrum of classic studies in social science, from experiments to the computational models, with a multidisciplinary approach. The book is suitable for those who want to get a picture of what it means to do social research today, and also to get an indication of the major open issues. The book is connected to a database of code for simulations, experimental data and allows to activate a subscription to a teaching tool using NetLogo, a programming language widely used in the social studies. The authors are researchers with first-hand experience research projects, both basic and applied. The work will be useful for those who want to understand more of the social, economic and political phenomena via computer applications.
This volume discusses the many recent significant developments, and identifies important problems, in the field of social indicators. In the last ten years the methodology of multivariate analysis and synthetic indicators construction significantly developed. In particular, starting from the classical theory of composite indicators many interesting approaches have been developed to overcome the weaknesses of composites. This volume focuses on these recent developments in synthesizing indicators, and more generally, in quantifying complex phenomena.
By now, most academics have heard something about the new science of complexity. In a manner reminiscent of Einstein and the last hundred years of physics, complexity science has captured the public imagination. ® One can go to Amazon. com and purchase books on complexification (Casti 1994), emergence (Holland 1998), small worlds (Barabási 2003), the web of life (Capra 1996), fuzzy thinking (Kosko 1993), global c- plexity (Urry 2003) and the business of long-tails (Anderson 2006). Even television has incorporated the topics of complexity science. Crime shows ® ® such as 24 or CSI typically feature investigators using the latest advances in computational modeling to “simulate scenarios” or “data mine” all p- sible suspects—all of which is done before the crime takes place. The ® World Wide Web is another example. A simple search on Google. Com using the phrase “complexity science” gets close to a million hits! C- plexity science is ubiquitous. What most scholars do not realize, however, is the remarkable role sociologists are playing in this new science. C- sider the following examples. 0. 1 Sociologists in Complexity Science The first example comes from the new science of networks (Barabási 2003). By now, most readers are familiar with the phenomena known as six-degrees of separation—the idea that, because most large networks are comprised of a significant number of non-random weak-ties, the nodes (e. g. , people, companies, etc.
Social systems are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible and natural language approaches inadequate for relating intricate cause and effect. However, individual- and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. Simulating Social Complexity examines all aspects of using agent- or individual-based simulation. This approach represents systems as individual elements having each their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes these elements "social" is that they are usefully interpretable as interacting elements of an observed society. In this, the focus is on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society. The phenomena of interest then result (emerge) from the dynamics of the interaction of social actors in an essential way and are usually not easily simplifiable by, for example, considering only representative actors. The introduction of accessible agent-based modelling allows the representation of social complexity in a more natural and direct manner than previous techniques. In particular, it is no longer necessary to distort a model with the introduction of overly strong assumptions simply in order to obtain analytic tractability. This makes agent-based modelling relatively accessible to a range of scientists. The outcomes of such models can be displayed and animated in ways that also make them more interpretable by experts and stakeholders. This handbook is intended to help in the process of maturation of this new field. It brings together, through the collaborative effort of many leading researchers, summaries of the best thinking and practice in this area and constitutes a reference point for standards against which future methodological advances are judged. This book will help those entering into the field to avoid "reinventing the wheel" each time, but it will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introductory, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section of ‘Further Reading’ briefly describing three to eight items that a newcomer might read next.
This book develops and presents a general social theory explaining social, cultural and economic ontology and, as a by-product, the ontology of other social institutions and structures. This theory is called social transaction theory. Using the framework of the complex adaptive systems model, this transdisciplinary social theory proposes that society, culture and economy are emergent from social and environmental transaction and negotiation. Each transaction contains an element of negotiation. With each transaction, there is continual renegotiation, however small or large. Even if the result is no change, renegotiation takes place. Thus, there is a constant emergence of social constructions and a continuous reconstruction of society in the ‘specious present.’ Practices, beliefs, explanations, and traditions become part of the accepted canon of a group through continual social transaction. Deviations from canon and expected outcomes are managed through narrative. Narrative can be either rejected or accepted into the social canon of a group or society. This social theory applied Bhaskar’s critical realism to refine the several theoretical works that were utilized. These include complex adaptive systems, Mead’s social theory, Maslow’s hierarchy of needs, Strauss’s negotiated order theory, game theory, Bruner’s narrative and folk psychology, Giddens's structuration theory and Ricoeur’s interpretation theory. A transdisciplinary account of the emergence of society and culture and the role of narrative, Complexity, Society and Social Transactions will appeal to scholars and practitioners of social theory and sociology.