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Big Data in Psychological Research by Sang Eun Woo,Louis Tay,Robert W. Proctor Pdf
Big Data in Psychological Research provides an overview of big data theory, research design and analysis, collection methods, applications, ethical concerns, best practices, and future research directions for psychologists.
Big Data in Psychological Research by Sang Eun Woo,Louis Tay (Psychologist),Robert W. Proctor Pdf
"Technological advances have led to an abundance of widely available data on every aspect of life today. Psychologists today have more information than ever before on human cognition, emotion, attitudes, and behavior. Big Data in Psychological Research addresses the opportunities and challenges that this data presents to psychological researchers. This edited collection provides an overview of theoretical approaches to the utility and purpose of big data, approaches to research design and analysis, collection methods, applications, limitations, best practice recommendations, and key issues related to privacy, security, and ethical concerns that are essential to understand for anyone working with big data. The book also discusses potential future research directions aimed at improving the quality and interpretation of big data projects, as well as the training and evaluation of psychological science teams that conduct research using big data"--
Big Data at Work by Scott Tonidandel,Eden B. King,Jose M. Cortina Pdf
The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.
The rapid advancements in technology, and our increasing interaction with it, have key implications for the field of psychology. The Psychology of Technology brings together research from different subdisciplines across psychology to address the ways in which technology and Big Data are changing how psychological research is conducted. It also examines how technology allows us to better understand human psychology. This text showcases cutting-edge research at the intersection of psychology and technology to provide an outlook into the future of psychological research in a tech-enabled world. The growing capabilities and reach of technology show no signs of abating, so it is critically important that psychology understand it and harness it effectively and ethically. Chapters offer fascinating and novel insights about the human condition using digital technologies as a window into human psychology, highlight the opportunities and challenges people face interacting with digital tech, and address the consequences of technology for individuals and societies. The intricacies of human-machine interaction, analyses of digital footprints, and "big data" approaches are investigated in detail.
Big Data in Cognitive Science by Michael N. Jones Pdf
While laboratory research is the backbone of collecting experimental data in cognitive science, a rapidly increasing amount of research is now capitalizing on large-scale and real-world digital data. Each piece of data is a trace of human behavior and offers us a potential clue to understanding basic cognitive principles. However, we have to be able to put the pieces together in a reasonable way, which necessitates both advances in our theoretical models and development of new methodological techniques. The primary goal of this volume is to present cutting-edge examples of mining large-scale and naturalistic data to discover important principles of cognition and evaluate theories that would not be possible without such a scale. This book also has a mission to stimulate cognitive scientists to consider new ways to harness big data in order to enhance our understanding of fundamental cognitive processes. Finally, this book aims to warn of the potential pitfalls of using, or being over-reliant on, big data and to show how big data can work alongside traditional, rigorously gathered experimental data rather than simply supersede it. In sum, this groundbreaking volume presents cognitive scientists and those in related fields with an exciting, detailed, stimulating, and realistic introduction to big data – and to show how it may greatly advance our understanding of the principles of human memory, perception, categorization, decision-making, language, problem-solving, and representation.
Parsing Psychology: Statistical and Computational Methods using Physiological, Behavioral, Social, and Cognitive Data by Pietro Cipresso,Jason C. Immekus Pdf
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Big Data for Qualitative Research by Kathy A. Mills Pdf
Big Data for Qualitative Research covers everything small data researchers need to know about big data, from the potentials of big data analytics to its methodological and ethical challenges. The data that we generate in everyday life is now digitally mediated, stored, and analyzed by web sites, companies, institutions, and governments. Big data is large volume, rapidly generated, digitally encoded information that is often related to other networked data, and can provide valuable evidence for study of phenomena. This book explores the potentials of qualitative methods and analysis for big data, including text mining, sentiment analysis, information and data visualization, netnography, follow-the-thing methods, mobile research methods, multimodal analysis, and rhythmanalysis. It debates new concerns about ethics, privacy, and dataveillance for big data qualitative researchers. This book is essential reading for those who do qualitative and mixed methods research, and are curious, excited, or even skeptical about big data and what it means for future research. Now is the time for researchers to understand, debate, and envisage the new possibilities and challenges of the rapidly developing and dynamic field of big data from the vantage point of the qualitative researcher.
Craig A. Hill,Paul P. Biemer,Trent D. Buskirk,Lilli Japec,Antje Kirchner,Stas Kolenikov,Lars E. Lyberg
Author : Craig A. Hill,Paul P. Biemer,Trent D. Buskirk,Lilli Japec,Antje Kirchner,Stas Kolenikov,Lars E. Lyberg Publisher : John Wiley & Sons Page : 784 pages File Size : 49,5 Mb Release : 2020-09-29 Category : Social Science ISBN : 9781118976326
Big Data Meets Survey Science by Craig A. Hill,Paul P. Biemer,Trent D. Buskirk,Lilli Japec,Antje Kirchner,Stas Kolenikov,Lars E. Lyberg Pdf
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
Author : Mike W. L. Cheung,Suzanne Jak Publisher : Unknown Page : 80 pages File Size : 41,6 Mb Release : 2019-03-11 Category : Big data ISBN : 0889375518
Big Data in Psychology by Mike W. L. Cheung,Suzanne Jak Pdf
Big data is becoming more prevalent in psychology and the behavioral sciences, and so are the methodological and statistical issues that arise from its use. Psychologists need to be equipped to deal with these. Big data can be generated in experimental studies where, for example, participants' physiological and psychological responses are tracked over time or where human brain imaging is employed. Observational data from websites such as Facebook, Twitter, and Google is also of increasing interest to psychologists. These sometimes huge data sets, which are often too large for standard computers and can also contain multiple types of data, bring with them challenging questions about data quality and the generalizability of the results as well as which statistical tools are suitable for analyzing them.The contributions in this volume explore these challenges, looking at the potential of applying machine learning techniques to big data in psychology as well as the split/analyze/meta-analyze (SAM) approach, which allows big data to be split up into smaller datasets so they can be analyzed with conventional multivariate techniques on standard computers. The issues of replicability, prediction accuracy, and combining types of data are also investigated.
Kali H. Trzesniewski,M. Brent Donnellan,Richard Eric Lucas
Author : Kali H. Trzesniewski,M. Brent Donnellan,Richard Eric Lucas Publisher : American Psychological Association (APA) Page : 264 pages File Size : 48,8 Mb Release : 2011 Category : Psychology ISBN : UOM:39076002904675
Secondary Data Analysis by Kali H. Trzesniewski,M. Brent Donnellan,Richard Eric Lucas Pdf
This wide-ranging yet practical book shows how the analysis of secondary data can provide unique opportunities for advancing psychological science. --Book Jacket.
Computational Social Psychology by Robin R. Vallacher,Stephen J. Read,Andrzej Nowak Pdf
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.
Social Cognition and Communication by Joseph P. Forgas,Orsolya Vincze,János László Pdf
Language is the essence of interpersonal behavior and social relationships, and it is social cognitive processes that determine how we produce and understand language. However, there has been surprisingly little interest in the past linking social cognition and communication. This book presents the latest cutting-edge research from a select group of leading international scholars investigating the how language shapes our thinking, and how social cognitive processes in turn influence language production and communication. The chapters represent diverse perspectives of investigating the links between language and communication, including evolutionary, linguistic, cognitive and affective approaches as well as the empirical analysis of written and spoken narratives. New methodologies are presented including the latest techniques of text analysis to illuminate the psychology of individual language users, and entire cultures and societies. The chapters address such questions as how are cognitive and identity processes reflected in language? How do affective states influence language production? Are political correctness norms in language use effective? How do partners manage to accommodate to each other’s communicative expectations? What is the role of language as a medium of interpersonal and intergroup influence? How are individual and cultural identities reflected in, and shaped by narratives in literature, school texts and the media? The book is aimed at all students, researchers and laypersons interested in the interplay between thinking and communication, and should be required reading for all professionals who use language in their everyday work to interact with people.
The Wiley-Blackwell Companion to Sociology by George Ritzer Pdf
Featuring a collection of original chapters by leading and emerging scholars, The Wiley-Blackwell Companion to Sociology presents a comprehensive and balanced overview of the major topics and emerging trends in the discipline of sociology today. Features original chapters contributed by an international cast of leading and emerging sociology scholars Represents the most innovative and 'state-of-the-art' thinking about the discipline Includes a general introduction and section introductions with chapters summaries by the editor
Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned. You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.
Big Data and Social Science by Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane Pdf
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.
