Introduction to Computational Social Science

This book PDF is perfect for those who love Computers genre, written by Claudio Cioffi-Revilla and published by Springer which was released on 29 June 2017 with total hardcover pages 636. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Introduction to Computational Social Science books below.

Introduction to Computational Social Science
Introduction to Computational Social Science
Author : Claudio Cioffi-Revilla
File Size : 54,9 Mb
Publisher : Springer
Language : English
Release Date : 29 June 2017
ISBN : 9783319501314
Pages : 636 pages
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Introduction to Computational Social Science by Claudio Cioffi-Revilla Book PDF Summary

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.

Introduction to Computational Social Science

Introduction to Computational Social Science by Claudio Cioffi-Revilla

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

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Doing Computational Social Science

Doing Computational Social Science by John McLevey

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

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Computational Social Science by R. Michael Alvarez

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

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Pathways Between Social Science and Computational Social Science

Pathways Between Social Science and Computational Social Science by Tamás Rudas,Gábor Péli

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

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Handbook of Computational Social Science Volume 1

Handbook of Computational Social Science Volume 1 by Uwe Engel,Anabel Quan-Haase,Sunny Xun Liu,Lars E Lyberg

"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

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Big Data in Computational Social Science and Humanities

Big Data in Computational Social Science and Humanities by Shu-Heng Chen

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,

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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

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Opportunities and Challenges for Computational Social Science Methods

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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

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