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Chapter 1 - Machine Learning Algorithms and Measurement

from Part I - Foundations

Published online by Cambridge University Press:  08 November 2023

By
Q. Chelsea Song ,
Ivan Hernandez ,
Hyun Joo Shin ,
Meaghan M. Tracy  and
Mengqiao Liu
Edited by
Louis Tay ,
Sang Eun Woo  and
Tara Behrend
Louis Tay
Affiliation:
Purdue University, Indiana
Sang Eun Woo
Affiliation:
Purdue University, Indiana
Tara Behrend
Affiliation:
Purdue University, Indiana
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Summary

This chapter provides an overview of the common machine learning algorithms used in psychological measurement (to measure human attributes). They include algorithms used to measure personality from interview videos; job satisfaction from open-ended text responses; and group-level emotions from social media posts and internet search trends. These algorithms enable effective and scalable measures of human psychology and behavior, driving technological advancements in measurement. The chapter consists of three parts. We first discuss machine learning and its unique contribution to measurement. We then provide an overview of the common machine learning algorithms used in measurement and their example applications. Finally, we provide recommendations and resources for using machine learning algorithms in measurement.

Keywords

machine learningpsychological measurementartificial intelligencesupervised learningunsupervised learning
Type
Chapter
Information
Technology and Measurement around the Globe , pp. 11 - 45
Publisher: Cambridge University Press
Print publication year: 2023

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