Three Models of Opinion Dynamics


Book Description

This Element develops an explanation of how and why all public policy preferences move over time.




The Dynamics of Public Opinion


Book Description

A central question in political representation is whether government responds to the people. To understand that, we need to know what the government is doing, and what the people think of it. We seek to understand a key question necessary to answer those bigger questions: How does American public opinion move over time? We posit three patterns of change over time in public opinion, depending on the type of issue. Issues on which the two parties regularly disagree provide clear partisan cues to the public. For these party-cue issues we present a slight variation on the thermostatic theory from (Soroka and Wlezien (2010); Wlezien (1995)); our “implied thermostatic model.” A smaller number of issues divide the public along lines unrelated to partisanship, and so partisan control of government provides no relevant clue. Finally, we note a small but important class of issues which capture response to cultural shifts.




Participatory Sensing, Opinions and Collective Awareness


Book Description

This book introduces and reviews recent advances in the field in a comprehensive and non-technical way by focusing on the potential of emerging citizen-science and social-computation frameworks, coupled with the latest theoretical and modeling tools developed by physicists, mathematicians, computer and social scientists to analyse, interpret and visualize complex data sets. There is overwhelming evidence that the current organisation of our economies and societies is seriously damaging biological ecosystems and human living conditions in the short term, with potentially catastrophic effects in the long term. The need to re-organise the daily activities with the greatest impact – energy consumption, transport, housing – towards a more efficient and sustainable development model has recently been raised in the public debate on several global, environmental issues. Above all, this requires the mismatch between global, societal and individual needs to be addressed. Recent advances in Information and Communication Technologies (ICT) can trigger important transitions at the individual and collective level to achieve this aim. Based on the findings of the collaborative research network EveryAware the following developments among the emerging ICT technologies are discussed in depth in this volume: • Participatory sensing – where ICT development is pushed to the level where it can support informed action at the hyperlocal scale, providing capabilities for environmental monitoring, data aggregation and mining, as well as information presentation and sharing. • Web gaming, social computing and internet-mediated collaboration – where the Web will continue to acquire the status of an infrastructure for social computing, allowing users’ cognitive abilities to be coordinated in online communities, and steering the collective action towards predefined goals. • Collective awareness and decision-making – where the access to both personal and community data, collected by users, processed with suitable analysis tools, and re-presented in an appropriate format by usable communication interfaces leads to a bottom-up development of collective social strategies.




Opinion Dynamics and the Evolution of Social Power in Social Networks


Book Description

This book uses rigorous mathematical analysis to advance opinion dynamics models for social networks in three major directions. First, a novel model is proposed to capture how a discrepancy between an individual’s private and expressed opinions can develop due to social pressures that arise in group situations or through extremists deliberately shaping public opinion. Detailed theoretical analysis of the final opinion distribution is followed by use of the model to study Asch’s seminal experiments on conformity, and the phenomenon of pluralistic ignorance. Second, the DeGroot-Friedkin model for evolution of an individual’s social power (self-confidence) is developed in a number of directions. The key result establishes that an individual’s initial social power is forgotten exponentially fast, even when the network changes over time; eventually, an individual’s social power depends only on the (changing) network structure. Last, a model for the simultaneous discussion of multiple logically interdependent topics is proposed. To ensure that a consensus across the opinions of all individuals is achieved, it turns out that the interpersonal interactions must be weaker than an individual’s introspective cognitive process for establishing logical consistency among the topics. Otherwise, the individual may experience cognitive overload and the opinion system becomes unstable. Conclusions of interest to control engineers, social scientists, and researchers from other relevant disciplines are discussed throughout the thesis with support from both social science and control literature.




Theory of Complexity


Book Description

Over two parts, this book examines the meaning of complexity in the context of systems both social and natural. Chapters cover such topics as the traveling salesman problem, models of opinion dynamics creation, a universal theory for knowledge formation in children, the evaluation of landscape organization and dynamics through information entropy indicators, and studying the performance of wind farms using artificial neural networks. We hope that this book will be useful to an audience interested in the different problems and approaches that are used within the theory of complexity




Proceedings of the 2019 International Conference of The Computational Social Science Society of the Americas


Book Description

This book presents the latest research into CSS methods, uses, and results, as presented at the 2019 annual conference of the CSSSA. This conference was held in Santa Fe, New Mexico, October 24 – 27, 2019, at the Drury Plaza Hotel. What follows is a diverse representation of new results and approaches for using the tools of CSS and agent-based modeling (ABM) for exploring complex phenomena across many different domains. Readers will therefore not only have the results of these specific projects on which to build, but will also gain a greater appreciation for the broad scope of CSS, and have a wealth of case-study examples that can serve as meaningful exemplars for new research projects and activities. The Computational Social Science Society of the Americas (CSSSA) is a professional society that aims to advance the field of CSS in all its areas, from fundamental principles to real-world applications, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing novel research findings.




Dynamics and Analysis of Alignment Models of Collective Behavior


Book Description

This book introduces a class of alignment models based on the so-called Cucker-Smale system as well as its kinetic and hydrodynamic counterparts. Cutting edge research in the area of collective behavior is presented, including emerging techniques from fluid mechanics, fractional analysis, and kinetic theory. Analytical aspects are highlighted throughout, such as regularity theory and long time behavior of solutions. Featuring open problems, readers will be motivated to apply these breakthrough methods to future research. The chapters offer an overview of state of the art research with introductions to core concepts. Chapter One introduces the central focus of the book: The agent-based Cucker-Smale system. Further agent-based systems and alignment systems are covered in chapters Two and Three. Following this are chapters covering the kinetic and hydrodynamic variants of the Cucker-Smale system. The core well-posedness theory of both smooth and singular models is then presented. Chapter Eight discusses the fully developed one-dimensional theory. The final chapter presents some of the known partial results concerning the regularity of multidimensional Euler Alignment systems. Dynamics and Analysis of Alignment Models of Collective Behavior is ideal for graduate students and researchers studying PDEs, especially those interested in the active areas of collective behavior and alignment models.




Distributed Control of Robotic Networks


Book Description

This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms. Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises. Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation




Opinion Dynamics in Social Networks


Book Description

Opinion dynamics is a complex procedure that entails a cognitive process when it deals with how a person integrates influential opinions to form revised opinion. Early research on opinion formation and social influence can be traced back to the eighteenth century. The original research focus was to study the conditions for people to aggregate information and reach consensus. Recently, due to the rise of the World Wide Web more and more studies tend to model opinion dynamics in large-scale social networks via computational methods. Among those works, non-Bayesian rule-of-thumb learning models keep gaining popularity due to their simplicity and computational efficiency. Unlike many non-Bayesian methods that treat individual opinions on various issues as independent beliefs but overlook the connections between knowledge fragments, we leverage from Bayesian approaches to consider opinions as a product inferred from one's knowledge-based system, where new knowledge fragments are acquired through social interaction and learning experiences. We study how an individual evaluates and adopts such knowledge fragments from others sources, both visible and invisible, on the basis of the findings from well-established social theories. A computational framework was developed to model opinion dynamics, in which we applied a probabilistic model named Bayesian Knowledge Bases to represent an individual's knowledge base. Opinion dynamics is studied by modeling opinion formation as a process of knowledge fusion, learning the impact metric that estimates the reliability of knowledge fragments, and identifying influential sources whose impact patterns are hidden. The contributions of this work can be summarized as 1) the development of a domain-independent computational method to model opinion formation by emphasizing the dependencies between knowledge pieces, 2) the capability to model different aspects of opinion dynamics in one entire system, 3) the intuitiveness in representing opinions such that the intents behind the opinion change can be readily captured, 4) the ability to characterize the influences in a social community by realizing and enriching theories of social communication, and 5) the flexibility of application on detecting and tracking hidden influential sources.




Sociophysics


Book Description

Do humans behave much like atoms? Sociophysics, which uses tools and concepts from the physics of disordered matter to describe some aspects of social and political behavior, answers in the affirmative. But advocating the use of models from the physical sciences to understand human behavior could be perceived as tantamount to dismissing the existence of human free will and also enabling those seeking manipulative skills . This thought-provoking book argues it is just the contrary. Indeed, future developments and evaluation will either show sociophysics to be inadequate, thus supporting the hypothesis that people can primarily be considered to be free agents, or valid, thus opening the path to a radically different vision of society and personal responsibility. This book attempts to explain why and how humans behave much like atoms, at least in some aspects of their collective lives, and then proposes how this knowledge can serve as a unique key to a dramatic leap forwards in achieving more social freedom in the real world. At heart, sociophysics and this book are about better comprehending the richness and potential of our social interaction, and so distancing ourselves from inanimate atoms.