TY - JOUR A1 - Munzert, Simon A1 - Ramirez-Ruiz, Sebastian A1 - Barberá, Pablo A1 - Guess, Andrew M. A1 - Yang, JungHwan T1 - Who’s cheating on your survey? A detection approach with digital trace data JF - Political Science Research and Methods N2 - 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. Y1 - 2022 UR - https://opus4.kobv.de/opus4-hsog/frontdoor/index/index/docId/4772 U6 - https://doi.org/10.1017/psrm.2022.42 SP - 1 EP - 9 ER -