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Big Data for Enhancing Measurement Quality

Item

Title
Big Data for Enhancing Measurement Quality
Abstract/Description
Big data offers a new frontier for psychological research. Although numerous articles and books have considered the general value of big data, it is necessary to delineate further the distinct sources of big data to develop a robust framework for how different types of big data may be useful for psychological research and under what circumstances. With this in mind, this chapter discusses several specific sources of big data that are potentially useful to psychological research. After extensively reviewing the existing literature (academic, practice oriented, news articles), the chapter identifies three major sources of big data as most frequently mentioned or used in current psychological research: social media (e.g., Twitter, Facebook), wearable sensors (e.g., sociometric badges, Fitbit), and Internet activities (e.g., Internet searches, page views). In addition, it considers two other emergent data sources that provide an increasing amount of accessible data: public network cameras and smartphones.
Date
2020
In publication
Big Data in Psychological Research
Editor
Woo, Sang Eun
Tay, Louis
Proctor, Robert W.
Pages
59-85
Publisher
American Psychological Association
Resource type
en
Medium
en Print
Background/context type
en Conceptual
Open access/free-text available
en No
Peer reviewed
en Yes
ISBN
978-1-4338-3167-6
978-1-4338-3233-8
Citation
Woo, S. E., Tay, L., Jebb, A. T., Ford, M. T., & Kern, M. L. (2020). Big Data for Enhancing Measurement Quality. In S. E. Woo, L. Tay, & R. W. Proctor (Eds.), Big Data in Psychological Research (pp. 59–85). American Psychological Association. https://doi.org/10.1037/0000193-004
Place
Washington, DC, US

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