![]() Participants were presented with a set of political headlines that varied on two dimensions: 1) They were either “fake news” (i.e., examples of headlines that have been determined to be false by fact-checkers) or “real news” (i.e., examples of true headlines that come from mainstream news sources) and 2) They were either good for the Democratic party in the United States (Pro-Democrat) or good for the Republican party (Pro-Republican), based on a pretest (discussed subsequently). The first published empirical study that used actual fake news headlines from social media as stimuli (see Figure 1 for representative examples) investigated the role of exposure (and, specifically, repetition) on belief in true and false news content (Pennycook et al., 2018). ![]() ![]() Nonetheless, aspects of this guide could easily be adapted to accommodate studies of full articles. The reason for this is that having participants read full news articles poses a host of methodological difficulties (e.g., do you allow people to decide how much of an article to read or try to enforce full attention?) and most people on social media do not typically read past the full headline anyway (Gabielkov et al., 2016). Furthermore, the guide is most relevant for studies of news headlines as opposed to full articles. Thus, although this is a practical guide to doing research on fake news and misinformation, it’s really a guide to doing behavioral research on “news” (or news-adjacent e.g., memes) content that has ecological validity because it is taken from the real world (as opposed to being constructed by researchers). 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.īy accident of history, the studies that use this design tend to focus on the phenomenon of “fake news” (i.e., news headlines that are fabricated but presented as if legitimate and spread on social media Lazer et al., 2018) however, one could use the same guide to create stimuli to test hypotheses using only true content from mainstream sources, or for false content that comes in other forms, etc. political issues and the COVID-19 pandemic. 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. 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. Steps are required if one wishes to present stimuli that allow generalization from the study to the real-world phenomenon of online misinformation. 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. This guide is intended to help researchers navigate the unique challenges that come with this type of research. inconsistent, etc.) and ask participants to make judgments (e.g., accuracy) or choices (e.g., whether they would share it on social media). These studies often present participants with news content that varies on relevant dimensions (e.g., true v. 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.
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