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Big Data in the Psychological Sciences [Kõva köide]

(University of Chicago)
  • Formaat: Hardback, 264 pages, kõrgus x laius x paksus: 254x203x16 mm, kaal: 801 g, Worked examples or Exercises
  • Ilmumisaeg: 23-Oct-2025
  • Kirjastus: Cambridge University Press
  • ISBN-10: 1009343580
  • ISBN-13: 9781009343589
  • Formaat: Hardback, 264 pages, kõrgus x laius x paksus: 254x203x16 mm, kaal: 801 g, Worked examples or Exercises
  • Ilmumisaeg: 23-Oct-2025
  • Kirjastus: Cambridge University Press
  • ISBN-10: 1009343580
  • ISBN-13: 9781009343589
Cutting-edge computational tools like artificial intelligence, data scraping, and online experiments are leading to new discoveries about the human mind. However, these new methods can be intimidating. This textbook demonstrates how Big Data is transforming the field of psychology, in an approachable and engaging way that is geared toward undergraduate students without any computational training. Each chapter covers a hot topic, such as social networks, smart devices, mobile apps, and computational linguistics. Students are introduced to the types of Big Data one can collect, the methods for analyzing such data, and the psychological theories we can address. Each chapter also includes discussion of real-world applications and ethical issues. Supplementary resources include an instructor manual with assignment questions and sample answers, figures and tables, and varied resources for students such as interactive class exercises, experiment demos, articles, and tools.

Arvustused

'From social media to sensors to AI, this book offers a brilliant tour of how the Big Data revolution is reshaping psychology. Accessible, inspiring, and grounded in real research problems, it walks students through everything from hands-on skills like web scraping, to big-picture theory testing, and even thoughtful discussions of ethics all presented with incredible clarity by one of the field's most inspiring new voices.' Timothy Brady, University of California, San Diego 'Exceptionally timely and comprehensive, Bainbridge's textbook deserves a place in every curriculum for behavioral methods. The chapters enhanced with interactive features and thought-provoking ethical questions are so engaging that they make me want to teach the course. And whether or not you work with Big Data, this is essential reading for all.' Marvin M. Chun, Yale University 'Combining conceptual depth and accessible writing, Bainbridge offers a timely contribution with a comprehensive overview of the field, covering definitions of Big Data in psychology and expertly navigating its key sources, methods, and analytical approaches. It addresses foundational topics, such as neuroimaging tools and statistical techniques, as well as emerging and contemporary discussions, including natural language processing, the development of large language models, and their applications in psychological research. It will resonate with a wide audience, from curious undergraduates to seasoned researchers looking to deepen their understanding of Big Data and its potential to reshape the psychological sciences.' Nemanja Vaci, University of Sheffield

Muu info

A student-friendly guide to computational methods and Big Data in psychology.
Preface;
1. What is big data?;
2. What is small data?;
3. Big
participant samples;
4. Big stimulus sets;
5. Big experiments;
6. Big
artificial intelligence;
7. Big human intelligence;
8. Big software: apps and
games;
9. Big hardware: sensors and physiological data;
10. Big brain data;
11. Big language;
12. Big social interactions; Index.
Wilma A. Bainbridge is an Associate Professor in the Department of Psychology at the University of Chicago. She has won the Association for Psychological Sciences Rising Stars Award (2023), an Alfred P. Sloan Fellowship in Neuroscience (2024), and the American Psychological Association's (APA) Distinguished Scientific Award for Early Career Contributions to Psychology (2025). Her research has garnered attention from outlets such as CNN, Vox, and Wired. She has previously edited two books on vision and memory, and her 'Big Data in Psychology' class has earned a Curricular Innovation Award from the University of Chicago.