Social Science

Simulation For The Social Scientist

Author: Gilbert, Nigel,Troitzsch, Klaus

Publisher: McGraw-Hill Education (UK)

ISBN: 0335225128

Category: Social Science

Page: 295

View: 4029

Social sciences -- Simulation methods. Social interaction -- Computer simulation. Social sciences -- Mathematical models. (publisher)
Social Science

Simulation For The Social Scientist

Author: Gilbert, Nigel,Troitzsch, Klaus

Publisher: McGraw-Hill Education (UK)

ISBN: 9780335216000

Category: Social Science

Page: 295

View: 1768

Social sciences -- Simulation methods. Social interaction -- Computer simulation. Social sciences -- Mathematical models. (publisher)
Social Science

Monte Carlo Simulation and Resampling Methods for Social Science

Author: Thomas M. Carsey,Jeffrey J. Harden

Publisher: SAGE Publications

ISBN: 1483324923

Category: Social Science

Page: 304

View: 1742

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.
Social Science

Agent-Based Models

Author: Nigel Gilbert,Professor Nigel Gilbert

Publisher: SAGE

ISBN: 1412949645

Category: Social Science

Page: 98

View: 2018

Aimed at readers with minimal experience in computer programming, this brief book provides a theoretical and methodological rationale for using ABM in the social sciences. It goes on to describe some carefully chosen examples from different disciplines, illustrating different approaches to ABM. It concludes with practical advice about how to design and create ABM, a discussion of validation procedures, and some guidelines about publishing articles based on ABM.

Theory Construction and Model-building Skills

A Practical Guide for Social Scientists

Author: James Jaccard,Jacob Jacoby

Publisher: Guilford Press

ISBN: 1606233408

Category: Psychology

Page: 391

View: 3245

Meeting a crucial need for graduate students and newly minted researchers, this innovative text provides hands-on tools for generating ideas and translating them into formal theories. It is illustrated with numerous practical examples drawn from multiple social science disciplines and research settings. The authors offer clear guidance for defining constructs, thinking through relationships and processes that link constructs, and deriving new theoretical models (or building on existing ones) based on those relationships. Step by step, they show readers how to use causal analysis, mathematical modeling, simulations, and grounded and emergent approaches to theory construction. A chapter on writing about theories contains invaluable advice on crafting effective papers and grant applications. Useful pedagogical features in every chapter include: Application exercises and concept exercises Lists of key terms and engaging topical boxes Annotated suggestions for further reading. This book is intended for graduate students in a range of disciplines, including psychology, education, sociology, health, and management, as well as social scientists pursing research careers in academic or other settings. It can serve as a primary text in graduate-level courses in theory construction or as a supplemental text in courses on research methodology, theories of a particular discipline, grant writing, or the dissertation.

Introduction to Computational Social Science

Principles and Applications

Author: Claudio Cioffi-Revilla

Publisher: Springer

ISBN: 3319501313

Category: Computers

Page: 618

View: 7338

This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.
Social Science

Tools and Techniques for Social Science Simulation

Author: Ramzi Suleiman,Klaus G. Troitzsch,Nigel Gilbert

Publisher: Springer Science & Business Media

ISBN: 3642517447

Category: Social Science

Page: 387

View: 3809

The use of computer simulations to study social phenomena has grown rapidly during the last few years. Many social scientists from the fields of economics, sociology, psychology and other disciplines now use computer simulations to study a wide range of social phenomena. The availability of powerful personal computers, the development of multidisciplinary approaches and the use of artificial intelligence models have all contributed to this development. The benefits of using computer simulations in the social sciences are obvious. This holds true for the use of simulations as tools for theory building and for its implementation as a tool for sensitivity analysis and parameter optimization in application-oriented models. In both, simulation provides powerful tools for the study of complex social systems, especially for dynamic and multi-agent social systems in which mathematical tractability is often impossible. The graphical display of simulation output renders it user friendly to many social scientists that lack sufficient familiarity with the language of mathematics. The present volume aims to contribute in four directions: (1) To examine theoretical and methodological issues related to the application of simulations in the social sciences. By this we wish to promote the objective of designing a unified, user-friendly, simulation toolkit which could be applied to diverse social problems. While no claim is made that this objective has been met, the theoretical issues treated in Part 1 of this volume are a contribution towards this objective.

Numerical Issues in Statistical Computing for the Social Scientist

Author: Micah Altman,Jeff Gill,Michael P. McDonald

Publisher: Wiley-Interscience

ISBN: 9780471236337

Category: Mathematics

Page: 323

View: 6839

At last—a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimation Integrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statistical procedures, and their applications in the field Replications and re-analysis of published social science research, using innovative numerical methods Key numerical estimation issues along with the means of avoiding common pitfalls A related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field.

Computational Modeling

Author: Charles S. Taber,Richard J. Timpone

Publisher: SAGE

ISBN: 9780803972704

Category: Computers

Page: 95

View: 9075

Computational modelling allows researchers to combine the rich detail of qualitative research with the rigour of quantitative and formal research, as well as to represent complex structures and processes within a theoretical model. After an introduction to modelling, the authors discuss the role of computational methods in the social sciences. They treat computational methods, including dynamic simulation, knowledge-based models and machine learning, as a single broad class of research tools and develop a framework for incorporating them within established traditions of social science research. They provide a concise description of each method and a variety of social science illustrations, including four detailed examples.

Social Emergence

Societies As Complex Systems

Author: Robert Keith Sawyer

Publisher: Cambridge University Press

ISBN: 9780521844642

Category: Philosophy

Page: 276

View: 9797

Can we understand important social issues by studying individual personalities and decisions? Or are societies somehow more than the people in them? Sociologists have long believed that psychology can't explain what happens when people work together in complex modern societies. In contrast, most psychologists and economists believe that if we have an accurate theory of how individuals make choices and act on them, we can explain pretty much everything about social life. Social Emergence takes a new approach to these longstanding questions. Sawyer argues that societies are complex dynamical systems, and that the best way to resolve these debates is by developing the concept of emergence, focusing on multiple levels of analysis - individuals, interactions, and groups - and with a dynamic focus on how social group phenomena emerge from communication processes among individual members. This book makes a unique contribution not only to complex systems research but also to social theory.
Social Science

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

Author: Scott M. Lynch

Publisher: Springer Science & Business Media

ISBN: 0387712658

Category: Social Science

Page: 359

View: 8099

This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.
Social Science

Agent-Based Computational Sociology

Author: Flaminio Squazzoni

Publisher: John Wiley & Sons

ISBN: 1119941636

Category: Social Science

Page: 248

View: 8184

Most of the intriguing social phenomena of our time, such as international terrorism, social inequality, and urban ethnic segregation, are consequences of complex forms of agent interaction that are difficult to observe methodically and experimentally. This book looks at a new research stream that makes use of advanced computer simulation modelling techniques to spotlight agent interaction that allows us to explain the emergence of social patterns. It presents a method to pursue analytical sociology investigations that look at relevant social mechanisms in various empirical situations, such as markets, urban cities, and organisations. This book: Provides a comprehensive introduction to epistemological, theoretical and methodological features of agent-based modelling in sociology through various discussions and examples. Presents the pros and cons of using agent-based models in sociology. Explores agent-based models in combining quantitative and qualitative aspects, and micro- and macro levels of analysis. Looks at how to pose an agent-based research question, identifying the model building blocks, and how to validate simulation results. Features examples of agent-based models that look at crucial sociology issues. Supported by an accompanying website featuring data sets and code for the models included in the book. Agent-Based Computational Sociology is written in a common sociological language and features examples of models that look at all the traditional explanatory challenges of sociology. Researchers and graduate students involved in the field of agent-based modelling and computer simulation in areas such as social sciences, cognitive sciences and computer sciences will benefit from this book.

Behavioral Computational Social Science

Author: Riccardo Boero

Publisher: John Wiley & Sons

ISBN: 1118657306

Category: Mathematics

Page: 200

View: 4804

"Provides a unified approach to social research, integrating both agent-based models and behavioral studies.Introduces the reader to all the concepts, tools and references that are required for conducting research in behavioral computational social science"--
Social Science

The Use of Models in the Social Sciences

Author: Lyndhurst Collins

Publisher: Routledge

ISBN: 1136444890

Category: Social Science

Page: 256

View: 3982

Tavistock Press was established as a co-operative venture between the Tavistock Institute and Routledge & Kegan Paul (RKP) in the 1950s to produce a series of major contributions across the social sciences. This volume is part of a 2001 reissue of a selection of those important works which have since gone out of print, or are difficult to locate. Published by Routledge, 112 volumes in total are being brought together under the name The International Behavioural and Social Sciences Library: Classics from the Tavistock Press. Reproduced here in facsimile, this volume was originally published in 1976 and is available individually. The collection is also available in a number of themed mini-sets of between 5 and 13 volumes, or as a complete collection.
Social Science

Analytical Sociology

Actions and Networks

Author: Gianluca Manzo

Publisher: John Wiley & Sons

ISBN: 1118762738

Category: Social Science

Page: 448

View: 1855

Demonstrates the power of the theoretical framework of analytical sociology in explaining a large array of social phenomena Analytical Sociology: Actions and Networks presents the most advanced theoretical discussion of analytical sociology, along with a unique set of examples on mechanism- based sociology. Leading scholars apply the theoretical principles of analytical sociology to understand how puzzling social and historical phenomena including crime, lynching, witch-hunts, tax behaviours, Web-based social movement and communication, restaurant reputation, job search and careers, social network homophily and instability, cooperation and trust are brought about by complex, multi-layered social mechanisms. The analyses presented in this book rely on a wide range of methods which include qualitative observations, advanced statistical techniques, complex network tools, refined simulation methods and creative experimental protocols. This book ultimately demonstrates that sociology, like any other science, is at its best when it dissects the mechanisms at work by means of rigorous model building and testing. Analytical Sociology: • Provides the most complete and up-to-date theoretical treatment of analytical sociology. • Looks at a wide range of complex social phenomena within a single and unitary theoretical framework. • Explores a variety of advanced methods to build and test theoretical models. • Examines how both computational modelling and experiments can be used to study the complex relation between norms, networks and social actions. • Brings together research from leading global experts in the field in order to present a unique set of examples on mechanism-based sociology. Advanced graduate students and researchers working in sociology, methodology of social sciences, statistics, social networks analysis and computer simulation will benefit from this book.
Business & Economics

What the Future Holds

Insights from Social Science

Author: Richard N. Cooper,Richard Layard

Publisher: MIT Press

ISBN: 9780262532044

Category: Business & Economics

Page: 285

View: 6106

Social scientists from various disciplines discuss and offer predictions about the future.
Social Science

Environmental Social Science

Human - Environment interactions and Sustainability

Author: Emilio F. Moran

Publisher: John Wiley & Sons

ISBN: 1444358278

Category: Social Science

Page: 232

View: 2516

Environmental Social Science offers a new synthesis of environmental studies, defining the nature of human-environment interactions and providing the foundation for a new cross-disciplinary enterprise that will make critical theories and research methods accessible across the natural and social sciences. Makes key theories and methods of the social sciences available to biologists and other environmental scientists Explains biological theories and concepts for the social sciences community working on the environment Helps bridge one of the difficult divides in collaborative work in human-environment research Includes much-needed descriptions of how to carry out research that is multinational, multiscale, multitemporal, and multidisciplinary within a complex systems theory context
Business & Economics

Generative Social Science: Studies in Agent-Based Computational Modeling

Studies in Agent-Based Computational Modeling

Author: Joshua M. Epstein

Publisher: Princeton University Press

ISBN: 1400842875

Category: Business & Economics

Page: 384

View: 4069

Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation. This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.

Science in the Age of Computer Simulation

Author: Eric Winsberg

Publisher: University of Chicago Press

ISBN: 0226902048

Category: Computers

Page: 152

View: 5468

Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? Eric Winsberg seeks to answer these questions in Science in the Age of Computer Simulation. Scrutinizing these issue with a philosophical lens, Winsberg explores the impact of simulation on such issues as the nature of scientific evidence; the role of values in science; the nature and role of fictions in science; and the relationship between simulation and experiment, theories and data, and theories at different levels of description. Science in the Age of Computer Simulation will transform many of the core issues in philosophy of science, as well as our basic understanding of the role of the digital computer in the sciences.
Business & Economics

Social Science Microsimulation

Author: Klaus G. Troitzsch

Publisher: Springer Science & Business Media

ISBN: 9783540615729

Category: Business & Economics

Page: 471

View: 575

This book gives an overview of the state of the art in five different approaches to social science simulation on the individual level. The volume contains microanalytical simulation models designed for policy implementation and evaluation, multilevel simulation methods designed for detecting emergent phenomena, dynamical game theory applications, the use of cellular automata to explain the emergence of structure in social systems, and multi-agent models using the experience from distributed artificial intelligence applied to special phenomena. The book collects the results of an international conference which brought together social scientists and computer scientists both engaged in a wide range of simulation approaches for the first time.