Advances In Computational Social Science
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| Author | : Uwe Engel |
| Publisher | : Taylor & Francis |
| Total Pages | : 417 |
| Release | : 2021-11-10 |
| Genre | : Computers |
| ISBN | : 1000448584 |
The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field but also encourages growth in new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientifi c and engineering sectors.
| Author | : Claudio Cioffi-Revilla |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 342 |
| Release | : 2013-12-31 |
| Genre | : Computers |
| ISBN | : 1447156617 |
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.
| Author | : National Academy of Engineering |
| Publisher | : National Academies Press |
| Total Pages | : 202 |
| Release | : 2007-03-08 |
| Genre | : Computers |
| ISBN | : 0309103398 |
This volume includes 15 papers from the National Academy of Engineering's 2006 U.S. Frontiers of Engineering (USFOE) Symposium held in September 2006. USFOE meetings bring together 100 outstanding engineers (ages 30 to 45) to exchange information about leading-edge technologies in a range of engineering fields. The 2006 symposium covered four topic areas: intelligent software systems and machines, the nano/bio interface, engineering personal mobility for the 21st century, and supply chain management. A paper by dinner speaker Dr. W. Dale Compton, Lillian M. Gilbreth Distinguished Professor of Industrial Engineering, Emeritus, is also included. The papers describe leading-edge research on commercializing auditory neuroscience, future developments in bionanotechnology, sustainable urban transportation, and managing disruptions to supply chains, among other topics. Appendixes include information about contributors, the symposium program, and a list of meeting participants. This is the twelfth volume in the USFOE series.
| Author | : Uwe Engel |
| Publisher | : Routledge |
| Total Pages | : 477 |
| Release | : 2021-11-10 |
| Genre | : Computers |
| ISBN | : 1000448622 |
The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This second volume focuses on foundations and advances in data science, statistical modeling, and machine learning. It covers a range of key issues, including the management of big data in terms of record linkage, streaming, and missing data. Machine learning, agent-based and statistical modeling, as well as data quality in relation to digital trace and textual data, as well as probability, non-probability, and crowdsourced samples represent further foci. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors.
| Author | : Tamás Rudas |
| Publisher | : Springer Nature |
| Total Pages | : 284 |
| Release | : 2021-01-22 |
| Genre | : Social Science |
| ISBN | : 3030549364 |
This volume shows that the emergence of computational social science (CSS) is an endogenous response to problems from within the social sciences and not exogeneous. The three parts of the volume address various pathways along which CSS has been developing from and interacting with existing research frameworks. The first part exemplifies how new theoretical models and approaches on which CSS research is based arise from theories of social science. The second part is about methodological advances facilitated by CSS-related techniques. The third part illustrates the contribution of CSS to traditional social science topics, further attesting to the embedded nature of CSS. The expected readership of the volume includes researchers with a traditional social science background who wish to approach CSS, experts in CSS looking for substantive links to more traditional social science theories, methods and topics, and finally, students working in both fields.
| Author | : Shu-Heng Chen |
| Publisher | : Springer |
| Total Pages | : 365 |
| Release | : 2014-05-22 |
| Genre | : Business & Economics |
| ISBN | : 4431548475 |
This volume is a post-conference publication of the 4th World Congress on Social Simulation (WCSS), with contents selected from among the 80 papers originally presented at the conference. WCSS is a biennial event, jointly organized by three scientific communities in computational social science, namely, the Pacific-Asian Association for Agent-Based Approach in Social Systems Sciences (PAAA), the European Social Simulation Association (ESSA), and the Computational Social Science Society of the Americas (CSSSA). It is, therefore, currently the most prominent conference in the area of agent-based social simulation. The papers selected for this volume give a holistic view of the current development of social simulation, indicating the directions for future research and creating an important archival document and milestone in the history of computational social science. Specifically, the papers included here cover substantial progress in artificial financial markets, macroeconomic forecasting, supply chain management, bank networks, social networks, urban planning, social norms and group formation, cross-cultural studies, political party competition, voting behavior, computational demography, computational anthropology, evolution of languages, public health and epidemics, AIDS, security and terrorism, methodological and epistemological issues, empirical-based agent-based modeling, modeling of experimental social science, gaming simulation, cognitive agents, and participatory simulation. Furthermore, pioneering studies in some new research areas, such as the theoretical foundations of social simulation and categorical social science, also are included in the volume.
| Author | : J. Kertész |
| Publisher | : IOS Press |
| Total Pages | : 212 |
| Release | : 2019-11-20 |
| Genre | : Social Science |
| ISBN | : 1643680374 |
For many years, the development of large-scale quantitative social science was hindered by a lack of data. Traditional methods of data collection like surveys were very useful, but were limited. The situation has of course changed with the development of computing and information communication technology, and we now live in a world of data deluge, where the question has become how to extract important information from the plethora of data that can be accessed. Big Data has made it possible to study societal questions which were once impossible to deal with, but new tools and new multidisciplinary approaches are required. Physicists, together with economists, sociologists, computer scientists, etc. have played an important role in their development. This book presents the 9 lectures delivered at the CCIII Summer Course Computational Social Science and Complex Systems, held as part of the International School of Physics Enrico Fermi in Varenna, Italy, from 16-21 July 2018. The course had the aim of presenting some of the recent developments in the interdisciplinary fields of computational social science and econophysics to PhD students and young researchers, with lectures focused on recent problems investigated in computational social science. Addressing some of the basic questions and many of the subtleties of the emerging field of computational social science, the book will be of interest to students, researchers and advanced research professionals alike.
| Author | : Abanoz, Enes |
| Publisher | : IGI Global |
| Total Pages | : 277 |
| Release | : 2022-03-18 |
| Genre | : Social Science |
| ISBN | : 1799885550 |
We are living in a digital era in which most of our daily activities take place online. This has created a big data phenomenon that has been subject to scientific research with increasingly available tools and processing power. As a result, a growing number of social science scholars are using computational methods for analyzing social behavior. To further the area, these evolving methods must be made known to sociological research scholars. Opportunities and Challenges for Computational Social Science Methods focuses on the implementation of social science methods and the opportunities and challenges of these methods. This book sheds light on the infrastructure that should be built to gain required skillsets, the tools used in computational social sciences, and the methods developed and applied into computational social sciences. Covering topics like computational communication, ecological cognition, and natural language processing, this book is an essential resource for researchers, data scientists, scholars, students, professors, sociologists, and academicians.
| Author | : Shu-Heng Chen |
| Publisher | : Springer |
| Total Pages | : 391 |
| Release | : 2018-11-21 |
| Genre | : Computers |
| ISBN | : 3319954652 |
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.
| Author | : Zining Yang |
| Publisher | : Springer Nature |
| Total Pages | : 403 |
| Release | : 2021-10-02 |
| Genre | : Science |
| ISBN | : 3030775178 |
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.
