Data Mining For The Social Sciences

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Data Mining For The Social Sciences
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Author : Paul Attewell
language : en
Publisher: Univ of California Press
Release Date : 2015-05-01
Data Mining For The Social Sciences written by Paul Attewell and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-01 with Social Science categories.
"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.
Knowledge Discovery In The Social Sciences
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Author : Prof. Xiaoling Shu
language : en
Publisher: Univ of California Press
Release Date : 2020-02-04
Knowledge Discovery In The Social Sciences written by Prof. Xiaoling Shu and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-04 with Social Science categories.
Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries
Data Mining For The Social Sciences
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Author : Paul Attewell
language : en
Publisher: Univ of California Press
Release Date : 2015-05
Data Mining For The Social Sciences written by Paul Attewell and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05 with Computers categories.
"The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.
Big Data Research For Social Sciences And Social Impact
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Author : Miltiadis D. Lytras
language : en
Publisher: MDPI
Release Date : 2020-03-19
Big Data Research For Social Sciences And Social Impact written by Miltiadis D. Lytras and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-19 with Technology & Engineering categories.
A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.
Big Data And Social Sciences Harnessing Databases For Political And Social Change
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Author : Edenilson Brandl
language : en
Publisher: Edenilson Brandl
Release Date :
Big Data And Social Sciences Harnessing Databases For Political And Social Change written by Edenilson Brandl and has been published by Edenilson Brandl this book supported file pdf, txt, epub, kindle and other format this book has been release on with Social Science categories.
The evolving landscape of social sciences has been profoundly transformed by the advent of big data and advanced computational methodologies. This text aims to bridge the gap between raw data abundance and meaningful social insight, underscoring the potential to harness data-driven approaches for understanding and influencing political and social dynamics. Central to this work is the recognition that traditional qualitative and quantitative methods, while foundational, are no longer sufficient to grapple with the scale, complexity, and velocity of contemporary social phenomena. The integration of big data analytics empowers researchers to analyze multilayered social interactions in unprecedented detail. This volume is designed to serve as a comprehensive resource for scholars, policymakers, and practitioners engaged in the intersection of data science and social inquiry. It advocates for a rigorous yet ethically grounded approach to data utilization, emphasizing methodological innovation balanced with social responsibility. The chapters herein address a broad spectrum of themes, from technical frameworks and analytic tools to applied case studies and ethical considerations, providing a multidimensional perspective on the possibilities and pitfalls inherent in big data applications within social contexts. In producing this work, attention was paid to fostering interdisciplinary dialogue, drawing upon insights from political science, sociology, computer science, and data ethics. It is through this synthesis that the book hopes to contribute to the emerging paradigm of computational social science. Ultimately, the goal is to equip readers with the conceptual frameworks and practical knowledge necessary to leverage big data in ways that promote equitable social change, enhance governance, and deepen the understanding of collective human behavior in an increasingly digitized world.
Big Data And Social Science
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Author : Ian Foster
language : en
Publisher: CRC Press
Release Date : 2020-11-17
Big Data And Social Science written by Ian Foster and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with Mathematics categories.
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.
Data Analytics For The Social Sciences
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Author : G. David Garson
language : en
Publisher: Routledge
Release Date : 2021-11-29
Data Analytics For The Social Sciences written by G. David Garson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Psychology categories.
Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.
Introduction To Computational Social Science
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Author : Claudio Cioffi-Revilla
language : en
Publisher: Springer
Release Date : 2017-06-29
Introduction To Computational Social Science written by Claudio Cioffi-Revilla and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-29 with Computers categories.
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.
Theoretical And Methodological Approaches To Social Sciences And Knowledge Management
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Author : Asunción Lopez-Varela Azcárate
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-08-16
Theoretical And Methodological Approaches To Social Sciences And Knowledge Management written by Asunción Lopez-Varela Azcárate and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-16 with Business & Economics categories.
This is a unique and groundbreaking collection of questions and answers coming from higher education institutions on diverse fields and across a wide spectrum of countries and cultures. It creates routes for further innovation, collaboration amidst the Sciences (both Natural and Social), the Humanities, and the private and public sectors of society. The chapters speak across sociocultural concerns, education, welfare and artistic sectors under the common desire for direct responses in more effective ways by means of interaction across societal structures.
Handbook Of Computational Social Science Volume 1
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Author : Uwe Engel
language : en
Publisher: Taylor & Francis
Release Date : 2021-11-10
Handbook Of Computational Social Science Volume 1 written by Uwe Engel and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-10 with Computers categories.
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.