Big Data in Psychological Research PDF Download

Author: Sang Eun Woo
Publisher: American Psychological Association (APA)
ISBN: 9781433831676
Category : Psychology
Languages : en
Pages : 0

View

Book Description
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.

Author: Sang Eun Woo
Publisher:
ISBN: 9781433832338
Category : Psychology
Languages : en
Pages :

View

Book Description
"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"--

Author: Scott Tonidandel
Publisher: Routledge
ISBN: 1317702697
Category : Psychology
Languages : en
Pages : 321

View

Book Description
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.

Author: Sandra Matz
Publisher: American Psychological Association (APA)
ISBN: 9781433836268
Category : Psychology
Languages : en
Pages : 320

View

Book Description
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.

Author: Michael N. Jones
Publisher: Psychology Press
ISBN: 1315413566
Category : Computers
Languages : en
Pages : 384

View

Book Description
The primary goal of this volume is to present cutting-edge examples of mining large and naturalistic datasets to discover important principles of cognition and to evaluate theories in a way that would not be possible without such scale. It explores techniques that have been underexploited by cognitive psychologists and explains how big data from numerous sources can inform researchers with different research interests and shed further light on how brain, cognition and behavior are interconnected. The book fills a major gap in the literature and has the potential to rapidly advance knowledge throughout the field. It is essential reading for any cognitive psychology researcher.

Author: Kathy A. Mills
Publisher: Routledge
ISBN: 0429509294
Category : Psychology
Languages : en
Pages : 78

View

Book Description
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.

Author: Craig A. Hill
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784

View

Book Description
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: Bill Lubanovic
Publisher: "O'Reilly Media, Inc."
ISBN: 1492051322
Category : Computers
Languages : en
Pages : 634

View

Book Description
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.

Author: Mike W. L. Cheung
Publisher:
ISBN: 9780889375512
Category : Big data
Languages : en
Pages : 80

View

Book Description
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.

Author: John J. McArdle
Publisher: Routledge
ISBN: 1135044090
Category : Psychology
Languages : en
Pages : 496

View

Book Description
This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different combinations of variables in large data sets. Methodological findings and conceptual models that explain reliable EDM techniques for predicting and understanding various risk mechanisms are integrated throughout. Numerous examples illustrate the use of these techniques in practice. Contributors provide insight through hands-on experiences with their own use of EDM techniques in various settings. Readers are also introduced to the most popular EDM software programs. A related website at http://mephisto.unige.ch/pub/edm-book-supplement/offers color versions of the book’s figures, a supplemental paper to chapter 3, and R commands for some chapters. The results of EDM analyses can be perilous – they are often taken as predictions with little regard for cross-validating the results. This carelessness can be catastrophic in terms of money lost or patients misdiagnosed. This book addresses these concerns and advocates for the development of checks and balances for EDM analyses. Both the promises and the perils of EDM are addressed. Editors McArdle and Ritschard taught the "Exploratory Data Mining" Advanced Training Institute of the American Psychological Association (APA). All contributors are top researchers from the US and Europe. Organized into two parts--methodology and applications, the techniques covered include decision, regression, and SEM tree models, growth mixture modeling, and time based categorical sequential analysis. Some of the applications of EDM (and the corresponding data) explored include: selection to college based on risky prior academic profiles the decline of cognitive abilities in older persons global perceptions of stress in adulthood predicting mortality from demographics and cognitive abilities risk factors during pregnancy and the impact on neonatal development Intended as a reference for researchers, methodologists, and advanced students in the social and behavioral sciences including psychology, sociology, business, econometrics, and medicine, interested in learning to apply the latest exploratory data mining techniques. Prerequisites include a basic class in statistics.