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200309t20202020dcua ob 001 0 eng |
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|a 2019054297
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|a DLC
|b eng
|e rda
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|c DLC
|d OCLCO
|d OCLCQ
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|d JSTOR
|d VLB
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|d OCLCA
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|d OCLCQ
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|a 1159243077
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|a 9781433832338
|q electronic book
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|b B54 2020
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|a UAMI
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245 |
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|a Big data in psychological research /
|c edited by Sang Eun Woo, Louis Tay, and Robert W. Proctor.
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|a Washington, DC :
|b American Psychological Association,
|c [2020]
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264 |
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|c ©2020
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300 |
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|a 1 online resource (ix, 469 pages) :
|b illustrations
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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504 |
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|a Includes bibliographical references and index.
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520 |
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|a "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"--
|c Provided by publisher.
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|a Description based on online resource; title from resource home page (ProQuest Ebook Central, viewed April 5, 2021).
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0 |
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|a Contributors -- Introduction -- I. Background and overview: Big data science : a philosophy of science perspective / Brian D. Haig. From small-scale experiments to big data : challenges and opportunities for experimental psychologists / Robert W. Proctor and Aiping Xiong. Big data for enhancing measurement quality / Sang Eun Woo, Louis Tay, Andrew T. Jebb, Michael T. Ford, and Margaret L. Kern -- II. Innovations in large-scale data collection and analysis techniques: Internet search and page view behavior scores : validity and usefulness as indicators of psychological states / Michael T. Ford. Observing human behavior through worldwide network cameras / Sara Aghajanzadeh, Andrew T. Jebb, Yifan Li, Yung-Hsiang Lu, and George K. Thiruvathukal. Wearable cameras, machine vision, and big data analytics : insights into people and the places they go / Andrew B. Blake, Daniel I. Lee, Roberto De La Rosa, and Ryne A. Sherman. Human-guided visual analytics for big data / Morteza Karimzadeh, Jieqiong Zhao, Guizhen Wang, Luke S. Snyder, and David S. Ebert. Human-guided visual analytics for big data / Morteza Karimzadeh, Jieqiong Zhao, Guizhen Wang, Luke S. Snyder, and David S. Ebert. Text mining : a field of opportunities / Padmini Srinivasan -- III. Applications: Big data in the science of learning / Sidney K. D'Mello. Big data in social psychology / Ivan Hernandez. Big data in health care delivery / Mohammad Adibuzzaman and Paul M. Griffin. The continued importance of theory : lessons from big data approaches to language and cognition / Brendan T. Johns, Randall K. Jamieson, and Michael N. Jones. Big data in developmental psychology / Kevin J. Grimm, Gabriela Stegmann, Ross Jacobucci, and Sarfaraz Serang. Applying principles of big data to the workplace and talent analytics / Q. Chelsea Song, Mengqiao Liu, Chen Tang, and Laura F. Long -- IV. Recommendations for responsible and rigorous use of big data: The Belmont Report in the age of big data : ethics at the intersection of psychological science and data science / Alexandra Paxton. Promoting robust and reliable big data research in psychology / Joshua A. Strauss and James A. Grand. Privacy and cybersecurity challenges, opportunities, and recommendations : personnel selection in an era of online application systems and big data / Talya N. Bauer, Donald M. Truxillo, Mark P. Jones, and Grant Brady. Privacy enhancing techniques for security / Elisa Bertino -- V. Concluding remarks: Future research directions for big data in psychology -- Index -- About the editors.
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590 |
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|a JSTOR
|b Books at JSTOR All Purchased
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590 |
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|a JSTOR
|b Books at JSTOR Demand Driven Acquisitions (DDA)
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650 |
|
0 |
|a Psychology
|x Research
|x Data processing.
|
650 |
|
0 |
|a Psychology
|x Research
|x Methodology.
|
650 |
|
0 |
|a Data mining.
|
650 |
|
0 |
|a Data sets.
|
650 |
1 |
2 |
|a Psychology
|x methods
|
650 |
2 |
2 |
|a Data Mining
|
650 |
2 |
2 |
|a Datasets as Topic
|
650 |
|
6 |
|a Psychologie
|x Recherche
|x Informatique.
|
650 |
|
6 |
|a Psychologie
|x Recherche
|x Méthodologie.
|
650 |
|
6 |
|a Exploration de données (Informatique)
|
650 |
|
6 |
|a Jeux de données.
|
650 |
|
7 |
|a PSYCHOLOGY / Research & Methodology
|2 bisacsh
|
650 |
|
7 |
|a Data sets.
|2 fast
|0 (OCoLC)fst02003345
|
650 |
|
7 |
|a Data mining.
|2 fast
|0 (OCoLC)fst00887946
|
650 |
|
7 |
|a Psychology
|x Research
|x Data processing.
|2 fast
|0 (OCoLC)fst01081508
|
650 |
|
7 |
|a Psychology
|x Research
|x Methodology.
|2 fast
|0 (OCoLC)fst01081515
|
700 |
1 |
|
|a Woo, Sang Eun,
|e editor.
|
700 |
1 |
|
|a Tay, Louis
|c (Psychologist),
|e editor.
|
700 |
1 |
|
|a Proctor, Robert W.,
|e editor.
|
776 |
0 |
8 |
|i Print version:
|t Big data in psychological research
|d Washington : American Psychological Association, 2020.
|z 9781433831676
|w (DLC) 2019054296
|
856 |
4 |
0 |
|u https://jstor.uam.elogim.com/stable/10.2307/j.ctv1chs5jz
|z Texto completo
|
938 |
|
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|a ProQuest Ebook Central
|b EBLB
|n EBL6233968
|
938 |
|
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|a YBP Library Services
|b YANK
|n 301346397
|
938 |
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|a EBSCOhost
|b EBSC
|n 2506159
|
994 |
|
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|a 92
|b IZTAP
|