Big Data in Cognitive Science (eBook, ePUB)

Redaktion: Jones, Michael N.

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 382
• Erscheinungstermin: 3. November 2016
• Englisch
• ISBN-13: 9781315413556
• Artikelnr.: 47134076

Autorenporträt

Michael N. Jones is the William and Katherine Estes Professor of Psychology, Cognitive Science, and Informatics at Indiana University, Bloomington, and the Editor-in-Chief of Behavior Research Methods. His research focuses on large-scale computational models of cognition, and statistical methodology for analyzing massive datasets to understand human behavior.

Inhaltsangabe

Developing Cognitive Theory by Mining Large-Scale Naturalistic Data
Michael N. Jones. Sequential Bayesian Updating for Big Data
Zita Oravecz
Matt Huentelman
& Joachim Vandekerckhove. Predicting and Improving Memory Retention: Psychological Theory Matters in the Big Data Era
Michael C. Mozer & Robert V. Lindsey. Tractable Bayesian Teaching
Baxter S. Eaves Jr.
April M. Schweinhart
& Patrick Shafto. Social Structure Relates to Linguistic Information Density
David W. Vinson & Rick Dale. Music Tagging and Listening: Testing the Memory Cue Hypothesis in a Collaborative Tagging System
Jared Lorince & Peter M. Todd. Flickr® Distributional Tagspace: Evaluating the Semantic Spaces Emerging from Flickr® Tags Distributions
Marianna Bolognesi. Large-Scale Network Representations of Semantics in the Mental Lexicon
Simon De Deyne
Yoed N. Kenett
David Anaki
Miriam Faust
& Dan Navarro. Individual Differences in Semantic Priming Performance: Insights from the Semantic Priming Project
Melvin J. Yap
Keith A. Hutchison
& Luuan Chin Tan. Small Worlds and Big Data: Examining the Simplification Assumption in Cognitive Modeling
Brendan Johns
Douglas J. K. Mewhort
& Michael N. Jones. Alignment in Web-based Dialogue: Who Aligns
and how Automatic is it? Studies in Big-Data Computational Psycholinguistics
David Reitter. Attention Economies
Information Crowding
and Language Change
Thomas T. Hills
James Adelman
& Takao Noguchi. Dcision by Sampling: Co Connecting Preferences to Real-World Regularities. Christopher Y. Olivola & Nick Chater.Crunching Big Data with Fingertips: How Typists Tune Their Performance Toward the Statistics of Natural Language
Lawrence P. Behmer Jr.
& Matthew J. C. Crump. Can Big Data Help Us Understand Human Vision?
Michael J. Tarr & Elissa M. Aminoff .