Leveraging Facebook targeted advertisments to study misinformation on social media

The ability to run targeted advertisements on popular social media platforms, such as Facebook, has enabled researchers to quickly obtain demographically and geographically diverse samples in response to research opportunities, at a very low cost. Moreover leveraging on samples obtained through social media platforms allows for studying social media users through survey experiments in situ rather than resorting to simulated environments and self-reported measures. On the downside, social media platforms, like Facebook, employ algorithms to optimize ad delivery by favouring users who are most likely to click on them and, as a result, the characteristics of the end samples are likely to differ from the underlying population. Since those algorithms are typically unknown, the most recent literature has focused on uncovering the hidden biases of ad delivery and correcting the end samples through quota sampling or post-stratification. The present paper aims to extend the literature by showing how the approaches proposed in the literature fare on typical multivariate analyses used to study the correlates as well as the effects of political misinformation on social media. In particular, the paper looks at the relationship between conspiracy beliefs and socio-political orientations, as well as conspiracy beliefs as the predictor of climate change denialism and compliance with government mandated policies in the context of the COVID-19 pandemic. To do so, the paper replicates the analyses conducted on survey data obtained through face-to-face interviews with samples collected via Facebook ads. The face-to-face data come from the 10th round of the European Social Survey which included both the democracy rotating module and a special COVID-19 related module that included questions about conspiracy beliefs. In addition to the insights about the role of conspiracy beliefs as a particular case of misinformation online, the results are likely to be useful for those who consider leveraging on the massive Facebook sampling frame for running surveys and survey experiments to study political misinformation among social media users.