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Overview
Full Product Details
Author: Michael N. Jones (Indiana Univetsity, USA)
Publisher: Taylor & Francis Ltd
Imprint: Psychology Press Ltd
Dimensions:
Width: 15.20cm
, Height: 2.30cm
, Length: 22.90cm
Weight: 0.521kg
ISBN: 9781138791930
ISBN 10: 1138791938
Pages: 374
Publication Date: 15 November 2016
Audience:
College/higher education
,
Professional and scholarly
,
Postgraduate, Research & Scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: In Print 
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Table of Contents
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.
Reviews
The advent of large-scale naturalistic data holds exciting promise for developing and testing cognitive theories. But while the challenge of collecting such data is no longer a major hurdle, analyzing and making sense of it is. This book, with contributions from pioneers in this effort, is a fantastic resource for cognitive scientists. -Jeffrey L. Elman, Chancellor's Associates Distinguished Professor of Cognitive Science, University of California, San Diego
The advent of large-scale naturalistic data holds exciting promise for developing and testing cognitive theories. But while the challenge of collecting such data is no longer a major hurdle, analyzing and making sense of it is. This book, with contributions from pioneers in this effort, is a fantastic resource for cognitive scientists. -Jeffrey L. Elman, Chancellor's Associates Distinguished Professor of Cognitive Science, University of California, San Diego
The advent of large-scale naturalistic data holds exciting promise for developing and testing cognitive theories. But while the challenge of collecting such data is no longer a major hurdle, analyzing and making sense of it is. This book, with contributions from pioneers in this effort, is a fantastic resource for cognitive scientists. -Jeffrey L. Elman, Chancellor’s Associates Distinguished Professor of Cognitive Science, University of California, San Diego
Author Information
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.
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