Computational Social Science

Discovery and Prediction

Author: R. Michael Alvarez

Publisher: Cambridge University Press

ISBN: 1316531287

Category: Political Science

Page: N.A

View: 9155

Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy.

Computational Social Science

Author: R. Michael Alvarez

Publisher: Cambridge University Press

ISBN: 1107107881

Category: Political Science

Page: 312

View: 8939

This book provides an overview of cutting-edge approaches to computational social science.

Computational Social Science

Discovery and Prediction

Author: R. Michael Alvarez

Publisher: Cambridge University Press

ISBN: 9781107518414

Category: Political Science

Page: 312

View: 9198

Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy.

Introduction to Computational Social Science

Principles and Applications

Author: Claudio Cioffi-Revilla

Publisher: Springer

ISBN: 3319501313

Category: Computers

Page: 618

View: 1827

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.

Big Data and Social Science

A Practical Guide to Methods and Tools

Author: Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane

Publisher: CRC Press

ISBN: 1498751431

Category: Mathematics

Page: 376

View: 4504

Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.

Behavioral Computational Social Science

Author: Riccardo Boero

Publisher: John Wiley & Sons

ISBN: 1118657306

Category: Mathematics

Page: 200

View: 2946

"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"--

Computational Social Psychology

Author: Robin R. Vallacher,Stephen J. Read,Andrzej Nowak

Publisher: Routledge

ISBN: 1351701681

Category: Psychology

Page: 398

View: 4149

Computational Social Psychology showcases a new approach to social psychology that enables theorists and researchers to specify social psychological processes in terms of formal rules that can be implemented and tested using the power of high speed computing technology and sophisticated software. This approach allows for previously infeasible investigations of the multi-dimensional nature of human experience as it unfolds in accordance with different temporal patterns on different timescales. In effect, the computational approach represents a rediscovery of the themes and ambitions that launched the field over a century ago. The book brings together social psychologists with varying topical interests who are taking the lead in this redirection of the field. Many present formal models that are implemented in computer simulations to test basic assumptions and investigate the emergence of higher-order properties; others develop models to fit the real-time evolution of people’s inner states, overt behavior, and social interactions. Collectively, the contributions illustrate how the methods and tools of the computational approach can investigate, and transform, the diverse landscape of social psychology.

Bit by Bit

Social Research in the Digital Age

Author: Matthew J. Salganik

Publisher: Princeton University Press

ISBN: 1400888182

Category: Social Science

Page: 448

View: 1928

An innovative and accessible guide to doing social research in the digital age In just the past several years, we have witnessed the birth and rapid spread of social media, mobile phones, and numerous other digital marvels. In addition to changing how we live, these tools enable us to collect and process data about human behavior on a scale never before imaginable, offering entirely new approaches to core questions about social behavior. Bit by Bit is the key to unlocking these powerful methods—a landmark book that will fundamentally change how the next generation of social scientists and data scientists explores the world around us. Bit by Bit is the essential guide to mastering the key principles of doing social research in this fast-evolving digital age. In this comprehensive yet accessible book, Matthew Salganik explains how the digital revolution is transforming how social scientists observe behavior, ask questions, run experiments, and engage in mass collaborations. He provides a wealth of real-world examples throughout and also lays out a principles-based approach to handling ethical challenges. Bit by Bit is an invaluable resource for social scientists who want to harness the research potential of big data and a must-read for data scientists interested in applying the lessons of social science to tomorrow’s technologies. Illustrates important ideas with examples of outstanding research Combines ideas from social science and data science in an accessible style and without jargon Goes beyond the analysis of “found” data to discuss the collection of “designed” data such as surveys, experiments, and mass collaboration Features an entire chapter on ethics Includes extensive suggestions for further reading and activities for the classroom or self-study

Quantitative Social Science

An Introduction

Author: Kosuke Imai

Publisher: Princeton University Press

ISBN: 1400885256

Category: Social Science

Page: 432

View: 9738

Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors. Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science Provides hands-on instruction using R programming, not paper-and-pencil statistics Includes more than forty data sets from actual research for students to test their skills on Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides

Big Data in Computational Social Science and Humanities

Author: Shu-Heng Chen

Publisher: Springer

ISBN: 9783319954646

Category: Computers

Page: 407

View: 8063

This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.

Making Social Sciences More Scientific

The Need for Predictive Models

Author: Rein Taagepera

Publisher: Oxford University Press

ISBN: 0199534667

Category: Political Science

Page: 254

View: 6250

Beyond Regression contrasts the predominance of statistics in today's social sciences and predominance of quantitatively predictive logical models in physics. It shows how to construct predictive models and gives social science examples. The book also shows how to use and report statistical analysis in more informative ways. This includes a shift to symmetric regression, instead of Ordinary Least Squares, which systematically underestimates the slopes oureyes (correctly) see. Beyond Regression is useful to students who wish to learn the basics of the scientific method and to all those researchers who look for ways to do better social science.

The SAGE Handbook of Social Media Research Methods

Author: Luke Sloan,Anabel Quan-Haase

Publisher: SAGE

ISBN: 1473987210

Category: Social Science

Page: 728

View: 3040

The SAGE Handbook of Social Media Research Methods offers a step-by-step guide to overcoming the challenges inherent in research projects that deal with 'big and broad data', from the formulation of research questions through to the interpretation of findings. The handbook includes chapters on specific social media platforms such as Twitter, Sina Weibo and Instagram, as well as a series of critical chapters. The holistic approach is organised into the following sections: Conceptualising & Designing Social Media Research Collection & Storage Qualitative Approaches to Social Media Data Quantitative Approaches to Social Media Data Diverse Approaches to Social Media Data Analytical Tools Social Media Platforms This handbook is the single most comprehensive resource for any scholar or graduate student embarking on a social media project.

Data Analysis Using Regression and Multilevel/Hierarchical Models

Author: Andrew Gelman,Jennifer Hill

Publisher: Cambridge University Press

ISBN: 9780521686891

Category: Mathematics

Page: 625

View: 8111

This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Behavior Computing

Modeling, Analysis, Mining and Decision

Author: Longbing Cao,Philip S. Yu

Publisher: Springer Science & Business Media

ISBN: 1447129695

Category: Computers

Page: 376

View: 9374

'Behavior' is an increasingly important concept in the scientific, societal, economic, cultural, political, military, living and virtual worlds. Behavior computing, or behavior informatics, consists of methodologies, techniques and practical tools for examining and interpreting behaviours in these various worlds. Behavior computing contributes to the in-depth understanding, discovery, applications and management of behavior intelligence. With contributions from leading researchers in this emerging field Behavior Computing: Modeling, Analysis, Mining and Decision includes chapters on: representation and modeling behaviors; behavior ontology; behaviour analysis; behaviour pattern mining; clustering complex behaviors; classification of complex behaviors; behaviour impact analysis; social behaviour analysis; organizational behaviour analysis; and behaviour computing applications. Behavior Computing: Modeling, Analysis, Mining and Decision provides a dedicated source of reference for the theory and applications of behavior informatics and behavior computing. Researchers, research students and practitioners in behavior studies, including computer science, behavioral science, and social science communities will find this state of the art volume invaluable.

Corrupt Research

The Case for Reconceptualizing Empirical Management and Social Science

Author: Raymond Hubbard

Publisher: SAGE Publications

ISBN: 1506305377

Category: Social Science

Page: 360

View: 7099

Addressing the immensely important topic of research credibility, Raymond Hubbard’s groundbreaking Corrupt Research proposes that we must treat such information with a healthy dose of skepticism. This book argues that the dominant model of knowledge procurement subscribed to in these areas—the significant difference paradigm—is philosophically suspect, methodologically impaired, and statistically broken. Hubbard introduces a more accurate, alternative framework—the significant sameness paradigm—for developing scientific knowledge. The majority of the book comprises a head-to-head comparison of the “significant difference” versus “significant sameness” conceptions of science across philosophical, methodological, and statistical perspectives.

Evaluating Elections

A Handbook of Methods and Standards

Author: R. Michael Alvarez,Lonna Rae Atkeson,Thad E. Hall

Publisher: Cambridge University Press

ISBN: 1107027624

Category: Political Science

Page: 173

View: 9136

"This book focuses on how the tools of public management and policy evaluation can be used to give election officials the data they need to improve elections"--Provided by publisher.

Computational Social Science in the Age of Big Data

Concepts, Methodologies, Tools, and Applications

Author: Martin Welker,Cathleen M. Stützer,Marc Egger

Publisher: Herbert von Halem Verlag

ISBN: 3869622687

Category: Business & Economics

Page: 460

View: 685

Der Sammelband Computational Social Science in the Age of Big Data beschäftigt sich mit Konzepten, Methoden, Tools und Anwendungen (automatisierter) datengetriebener Forschung mit sozialwissenschaftlichem Hintergrund. Der Fokus des Bandes liegt auf der Etablierung der Computational Social Science (CSS) als aufkommendes Forschungs- und Anwendungsfeld. Es werden Beiträge international namhafter Autoren präsentiert, die forschungs- und praxisrelevante Themen dieses Bereiches besprechen. Die Herausgeber forcieren dabei einen interdisziplinären Zugang zum Feld, der sowohl Online-Forschern aus der Wissenschaft wie auch aus der angewandten Marktforschung einen Einstieg bietet.

Multidimensional Item Response Theory

Author: M.D. Reckase

Publisher: Springer Science & Business Media

ISBN: 9780387899763

Category: Social Science

Page: 354

View: 7658

First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing

Causality

Author: Judea Pearl

Publisher: Cambridge University Press

ISBN: 1139643983

Category: Science

Page: N.A

View: 3369

Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence (AI) and systems from The Cognitive Science Society.