Introduction to Computational Social Science

Introduction to Computational Social Science

Author: Claudio Cioffi-Revilla

Publisher: Springer Science & Business Media

Published: 2013-12-31

Total Pages: 342

ISBN-13: 1447156617

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This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.


Computer Applications in the Social Sciences

Computer Applications in the Social Sciences

Author: Edward E. Brent

Publisher: Temple University Press

Published: 1990

Total Pages: 506

ISBN-13: 9780877226666

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Presenting an introduction to computing and advice on computer applications, this book examines hardware and software with respect to the needs of the social scientist. It offers a framework for the use of computers, with focus on the 'work station', the center of which is a personal computer connected to networks by a telephone-based modem.


Doing Computational Social Science

Doing Computational Social Science

Author: John McLevey

Publisher: SAGE

Published: 2021-12-15

Total Pages: 689

ISBN-13: 1529736706

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Computational approaches offer exciting opportunities for us to do social science differently. This beginner’s guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed. For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.


Computing in the Social Sciences and Humanities

Computing in the Social Sciences and Humanities

Author: Orville Vernon Burton

Publisher: University of Illinois Press

Published: 2002

Total Pages: 220

ISBN-13: 9780252026850

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CD-ROm contains: Multimedia that provides unique approach to various disciplines in the social sciences and humanities -- Links to related resources.


Social Science, Technical Systems, and Cooperative Work

Social Science, Technical Systems, and Cooperative Work

Author: Geoffrey Bowker

Publisher: Psychology Press

Published: 2014-05-12

Total Pages: 495

ISBN-13: 1317778766

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This book is the first to directly address the question of how to bridge what has been termed the "great divide" between the approaches of systems developers and those of social scientists to computer supported cooperative work--a question that has been vigorously debated in the systems development literature. Traditionally, developers have been trained in formal methods and oriented to engineering and formal theoretical problems; many social scientists in the CSCW field come from humanistic traditions in which results are reported in a narrative mode. In spite of their differences in style, the two groups have been cooperating more and more in the last decade, as the "people problems" associated with computing become increasingly evident to everyone. The authors have been encouraged to examine, rigorously and in depth, the theoretical basis of CSCW. With contributions from field leaders in the United Kingdom, France, Scandinavia, Mexico, and the United States, this volume offers an exciting overview of the cutting edge of research and theory. It constitutes a solid foundation for the rapidly coalescing field of social informatics. Divided into three parts, this volume covers social theory, design theory, and the sociotechnical system with respect to CSCW. The first set of chapters looks at ways of rethinking basic social categories with the development of distributed collaborative computing technology--concepts of the group, technology, information, user, and text. The next section concentrates more on the lessons that can be learned at the design stage given that one wants to build a CSCW system incorporating these insights--what kind of work does one need to do and how is understanding of design affected? The final part looks at the integration of social and technical in the operation of working sociotechnical systems. Collectively the contributors make the argument that the social and technical are irremediably linked in practice and so the "great divide" not only should be a thing of the past, it should never have existed in the first place.


Big Data in Computational Social Science and Humanities

Big Data in Computational Social Science and Humanities

Author: Shu-Heng Chen

Publisher: Springer

Published: 2018-11-21

Total Pages: 391

ISBN-13: 3319954652

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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.


Programming with Python for Social Scientists

Programming with Python for Social Scientists

Author: Phillip D. Brooker

Publisher: SAGE

Published: 2019-12-09

Total Pages: 370

ISBN-13: 1526486342

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As data become ′big′, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of - and control over - how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including: the fundamentals of why and how to do your own programming in social scientific research, questions of ethics and research design, a clear, easy to follow ′how-to′ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more. Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis.


Social Science for What?

Social Science for What?

Author: Mark Solovey

Publisher: MIT Press

Published: 2020-07-07

Total Pages: 409

ISBN-13: 0262358751

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How the NSF became an important yet controversial patron for the social sciences, influencing debates over their scientific status and social relevance. In the early Cold War years, the U.S. government established the National Science Foundation (NSF), a civilian agency that soon became widely known for its dedication to supporting first-rate science. The agency's 1950 enabling legislation made no mention of the social sciences, although it included a vague reference to "other sciences." Nevertheless, as Mark Solovey shows in this book, the NSF also soon became a major--albeit controversial--source of public funding for them.


Human-Computer Interaction and Technology Integration in Modern Society

Human-Computer Interaction and Technology Integration in Modern Society

Author: Rahman, Hakikur

Publisher: IGI Global

Published: 2021-02-19

Total Pages: 347

ISBN-13: 1799858510

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Technology has opened a wide window of novel communication methods and techniques and has become ubiquitous in modern society. With advancements occurring rapidly and transforming practices and efficiencies within all fields including business, education, medicine, engineering, and so on, it is important to remain up to date on the latest research findings. Human-Computer Interaction and Technology Integration in Modern Society is a critical reference source that examines the integration of technological innovations into every aspect of modern society including education and business. Highlighting important topics that include digitization, human development, knowledge management, and open innovation, this book is ideal for IT specialists, policymakers, professionals, academicians, researchers, practitioners, and students.


Web Social Science

Web Social Science

Author: Robert Ackland

Publisher: SAGE

Published: 2013-06-17

Total Pages: 258

ISBN-13: 1446283119

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Although written simply enough to be accessible to undergraduates, accomplished scholars are likely to appreciate it too. Reading it taught me quite a lot about a subject I thought I knew rather well. - Paul Vogt, Illinois State University "This book brings the art and science of building and applying innovative online research tools to students and faculty across the social sciences." - William H. Dutton, University of Oxford A comprehensive guide to the theory and practice of web Social Science. This book demonstrates how the web is being used to collect social research data, such as online surveys and interviews, as well as digital trace data from social media environments, such as Facebook and Twitter. It also illuminates how the advent of the web has led to traditional social science concepts and approaches being combined with those from other scientific disciplines, leading to new insights into social, political and economic behaviour. Situating social sciences in the digital age, this book aids: understanding of the fundamental changes to society, politics and the economy that have resulted from the advent of the web choice of appropriate data, tools and research methods for conducting research using web data learning how web data are providing new insights into long-standing social science research questions appreciation of how social science can facilitate an understanding of life in the digital age It is ideal for students and researchers across the social sciences, as well as those from information science, computer science and engineering who want to learn about how social scientists are thinking about and researching the web.