Big Data In Psychology Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Big Data In Psychology book. This book definitely worth reading, it is an incredibly well-written.
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.
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.
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.
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.
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 : 51,9 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 : 51,6 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.
Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences by John J. McArdle,Gilbert Ritschard Pdf
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.
Strategy Beyond the Hockey Stick by Chris Bradley,Martin Hirt,Sven Smit Pdf
Beat the odds with a bold strategy from McKinsey & Company "Every once in a while, a genuinely fresh approach to business strategy appears" —legendary business professor Richard Rumelt, UCLA McKinsey & Company's newest, most definitive, and most irreverent book on strategy—which thousands of executives are already using—is a must-read for all C-suite executives looking to create winning corporate strategies. Strategy Beyond the Hockey Stick is spearheading an empirical revolution in the field of strategy. Based on an extensive analysis of the key factors that drove the long-term performance of thousands of global companies, the book offers a ground-breaking formula that enables you to objectively assess your strategy's real odds of future success. "This book is fundamental. The principles laid out here, with compelling data, are a great way around the social pitfalls in strategy development." —Frans Van Houten, CEO, Royal Philips N.V. The authors have discovered that over a 10-year period, just 1 in 12 companies manage to jump from the middle tier of corporate performance—where 60% of companies reside, making very little economic profit—to the top quintile where 90% of global economic profit is made. This movement does not happen by magic—it depends on your company's current position, the trends it faces, and the big moves you make to give it the strongest chance of vaulting over the competition. This is not another strategy framework. Rather, Strategy Beyond the Hockey Stick shows, through empirical analysis and the experiences of dozens of companies that have successfully made multiple big moves, that to dramatically improve performance, you have to overcome incrementalism and corporate inertia. "A different kind of book—I couldn't put it down. Inspiring new insights on the facts of what it takes to move a company's performance, combined with practical advice on how to deal with real-life dynamics in management teams." —Jane Fraser, CEO, Citigroup Latin America
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 : 55,9 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.
Big Data in Computational Social Science and Humanities by Shu-Heng Chen Pdf
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.
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.
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.
