Misinformation poses a significant threat to managing global challenges such as COVID-19, climate change, and immigration. Prior research shows that individuals with conservative and far-right ideology are more likely to share misinformation on social media and more resistant to fact-checks, than moderates or liberals (Grinberg et al., 2019). In addition, past studies have reported that in comparison to liberals, conservatives exhibit lower scores in cognitive flexibility (the ability to incorporate new information into behavioural sequences) and reduced neural markers of cognitive conflict during executive tasks (Amodio et al., 2007). This leads to the hypothesis that cognitive (in)flexibility is a relevant predictor of misinformation sharing on social media. We propose to address precisely this hypothesis.

This project is a cross-disciplinary collaboration between IMIM and DTIC-CBC, based on a pre-existing synergy; the aim is to combine neuroscience and social research on ideological polarisation in the context of social media, address its causes and consequences, and the possibility to understand and modulate its cognitive mechanisms. Specifically, this project  builds on the project “Neurocognitive basis of misinformation sharing across the political spectrum”, recently awarded to our groups (BIAL Foundation), where we will test, in an EEG laboratory study, whether propensity to misinformation sharing amongst conservatives and liberals is correlated to neural markers of cognitive flexibility. This MdM project expands this research in two important ways: (1) testing, in a field study, whether the relationship between cognitive flexibility and engagement with misinformation holds under ecologically valid online environments, and (2) evaluating whether cognitive flexibility moderates people’s adaptation to changes in the their online social media environments.

Amodio, D. M. et al. (2007). Neurocognitive correlates of liberalism and conservatism. Nat Neurosci, 10(10), 1246–1247.

Grinberg, N. et al. (2019). Fake news on Twitter during the 2016 U.S. presidential election. Science, 363(6425), 374–378.