In this note, we provide direct evidence of cheating in online assessments of political knowledge. We combine survey responses with web tracking data of a German and a US online panel to assess whether people turn to external sources for answers. We observe item-level prevalence rates of cheating that range from 0 to 12 percent depending on question type and difficulty, and find that 23 percent of respondents engage in cheating at least once across waves. In the US panel, which employed a commitment pledge, we observe cheating behavior among less than 1 percent of respondents. We find robust respondent- and item-level characteristics associated with cheating. However, item-level instances of cheating are rare events; as such, they are difficult to predict and correct for without tracking data. Even so, our analyses comparing naive and cheating-corrected measures of political knowledge provide evidence that cheating does not substantially distort inferences.

Digital literacy is receiving increased scholarly attention as a potential explanatory factor in the spread of misinformation and other online pathologies. As a concept, however, it remains surprisingly elusive, with little consensus on definitions or measures. We provide a digital literacy framework for political scientists and test survey items to measure it with an application to online information retrieval tasks. There exists substantial variation in levels of digital literacy in the population, which we show is correlated with age and could confound observed relationships. However, this is obscured by researchers’ reliance on online convenience samples that select for people with computer and internet skills. We discuss the implications of these measurement and sample selection considerations for effect heterogeneity in studies of online political behavior. We argue that there is no universally applicable formula for selecting a given non-probability sample or operationalization of the concept of digital literacy; instead, we conclude, researchers should make theoretically informed arguments about how they select both sample and measure.

Discussions around declining trust in the US media can be vague about its effects. One classic answer comes from the persuasion literature, in which source credibility plays a key role. However, existing research almost universally takes credibility as a given. To overcome the potentially severe confounding that can result from this, we create a hypothetical news outlet and manipulate to what extent it is portrayed as credible. We then randomly assign subjects to read op-eds attributed to the source. Our credibility treatments are strong, increasing trust in our mock source until up to 10 days later. We find some evidence that the resulting higher perceived credibility boosts the persuasiveness of arguments about more partisan topics (but not for a less politicized issue). Though our findings are mixed, we argue that this experimental approach can fruitfully enhance our understanding of the interplay between source trust and opinion change over sustained periods.

Political elites sometimes seek to delegitimize election results using unsubstantiated claims of fraud. Most recently, Donald Trump sought to overturn his loss in the 2020 US presidential election by falsely alleging widespread fraud. Our study provides new evidence demonstrating the corrosive effect of fraud claims like these on trust in the election system. Using a nationwide survey experiment conducted after the 2018 midterm elections – a time when many prominent Republicans also made unsubstantiated fraud claims – we show that exposure to claims of voter fraud reduces confidence in electoral integrity, though not support for democracy itself. The effects are concentrated among Republicans and Trump approvers. Worryingly, corrective messages from mainstream sources do not measurably reduce the damage these accusations inflict. These results suggest that unsubstantiated voter-fraud claims undermine confidence in elections, particularly when the claims are politically congenial, and that their effects cannot easily be mitigated by fact-checking.

Self-reported measures of media exposure are plagued with error and questions about validity. Since they are essential to studying media effects, a substantial literature has explored the shortcomings of these measures, tested proxies, and proposed refinements. But lacking an objective baseline, such investigations can only make relative comparisons. By focusing specifically on recent Internet activity stored by Web browsers, this article's methodology captures individuals' actual consumption of political media. Using experiments embedded within an online survey, I test three different measures of media exposure and compare them to the actual exposure. I find that open-ended survey prompts reduce overreporting and generate an accurate picture of the overall audience for online news. I also show that they predict news recall at least as well as general knowledge. Together, these results demonstrate that some ways of asking questions about media use are better than others. I conclude with a discussion of survey-based exposure measures for online political information and the applicability of this article's direct method of exposure measurement for future studies.