Description and purpose
MiMeSys centers on information disorder and ideological and affective polarization as crucial sources of misperceptions among citizens and targets the effects of these misperceptions on relevant political attitudes and behaviours. The project focuses on a number of critical issues that have posed fundamental challenges in both Italy and Europe in recent years: the Covid-19 pandemic, the Russian-Ukrainian war and the resulting refugee crisis, climate change, and gender equality.
Website: https://www.mimesys-project.it

Purpose
The project aims to achieve its goals through a cutting-edge and multi-method research design based on a panel survey including experiments, an elite survey, social and traditional media analysis and in-depth interviews. Thus, MiMeSys significantly advances scientific knowledge on the causes and the political implications of misperceptions generating high-quality results that will benefit not only the academic community but also media professionals, and the public-at-large.
Expected results
- Assessment of the impact of disinformation and polarization on citizens' political attitudes and behaviors through citizen surveys.
- Assessment of misperceptions among the media and political elites through surveys of journalists and politicians.
- Assessment of forms of disinformation and polarization conveyed by traditional media and social media through content analysis of print newspapers and online platforms.
Achieved results
- A representative sample of 2,408 citizens was surveyed in three waves between June and July 2024.
- A sample of 1,066 politicians and journalists was interviewed in March 2025 on information diet, misperceptions and polarization.
- A corpus of 21,592 newspaper articles (2020-2024) covering information disorder and political parties/leaders from five Italian newspapers was collected and processed.
- A corpus of over 20,000 social media posts (2020-2024) was collected and processed, including content from the same newspapers and leaders analyzed in the press dataset.