A Practical Guide to Doing Behavioral Research on Fake News and Misinformation
Name
collabra_2021_7_1_25293.pdf
Description
Published version
Size
665.5 KB
Format
Adobe PDF
Checksum (MD5)
0dca1a04af590a4f7e8a7fee0a9d9739
Author(s)
Pennycook, Gordon
Binnendyk, Jabin
Newton, Christie
Rand, David G
Date Issued
2021
Journal
Collabra: Psychology
Publisher
University of California Press
Citation
Pennycook, Gordon, Binnendyk, Jabin, Newton, Christie and Rand, David G. 2021. "A Practical Guide to Doing Behavioral Research on Fake News and Misinformation." Collabra: Psychology, 7 (1).
Version
Final published version
Abstract
Coincident with the global rise in concern about the spread of misinformation on social media, there has been influx of behavioral research on so-called “fake news” (fabricated or false news headlines that are presented as if legitimate) and other forms of misinformation. These studies often present participants with news content that varies on relevant dimensions (e.g., true v. false, politically consistent v. inconsistent, etc.) and ask participants to make judgments (e.g., accuracy) or choices (e.g., whether they would share it on social media). This guide is intended to help researchers navigate the unique challenges that come with this type of research. Principle among these issues is that the nature of news content that is being spread on social media (whether it is false, misleading, or true) is a moving target that reflects current affairs in the context of interest. Steps are required if one wishes to present stimuli that allow generalization from the study to the real-world phenomenon of online misinformation. Furthermore, the selection of content to include can be highly consequential for the study’s outcome, and researcher biases can easily result in biases in a stimulus set. As such, we advocate for pretesting materials and, to this end, report our own pretest of 224 recent true and false news headlines, both relating to U.S. political issues and the COVID-19 pandemic. These headlines may be of use in the short term, but, more importantly, the pretest is intended to serve as an example of best practices in a quickly evolving area of research.
MIT Department
Sloan School of Management
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1525/COLLABRA.25293
