Abstract

The COVID-19 pandemic highlighted the critical issue of misinformation, sparking interest in the field of infodemiology, which examines the spread and impact of information on public health perceptions. Social media platforms, particularly Twitter, have been instrumental in both the dissemination and mitigation of misinformation related to COVID-19. This study investigates the relationship between geographic location and public perception of COVID-19 information across 10 Italian cities in the north, center, south, and islands. By analyzing geographically tagged Twitter data this study analyzes COVID-19 discourse. Our network analysis examines user interactions through a filtered network of 4,792 high-degree nodes, identifying key information spreaders and community structures. Through spatiotemporal mapping across Italian regions, we analyze how geographic and temporal factors correlate with information patterns, socially prevalent narratives and how key public personalities influence social media discourse. This multi-dimensional analysis reveals regional variations in COVID-19 discourse and public response patterns, offering insights into how location-specific factors shape public health communication dynamics during crises. This research informs strategies for targeted information campaigns, helping public health agencies to better address misinformation in specific geographic contexts and ultimately improve community resilience during health emergencies. 

Keywords: Infodemiology; Covid-19 Misinformation; Geospatial Analysis; Public Perception; Social Media Analysis; Italy; Twitter 

Tools Used

• Python libraries - numpy, pandas, sklearn, seaborn, matplotlib, networkx

• Microsoft Excel - Data Processing