Modelling Infodemics on a Global Scale: A 30 Countries Study using Epidemiological and Social Listening Data

Fuente: arXiv
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Autores principales: Loru, Edoardo, Delmastro, Marco, Gesualdo, Francesco, Cinelli, Matteo
Formato: Preprint
Publicado: 2025
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author Loru, Edoardo
Delmastro, Marco
Gesualdo, Francesco
Cinelli, Matteo
author_facet Loru, Edoardo
Delmastro, Marco
Gesualdo, Francesco
Cinelli, Matteo
contents Infodemics are a threat to public health, arising from multiple interacting phenomena occurring both online and offline. The continuous feedback loops between the digital information ecosystem and offline contingencies make infodemics particularly challenging to define operationally, measure, and eventually model in quantitative terms. In this study, we present evidence of the effect of various epidemic-related variables on the dynamics of infodemics, using a robust modelling framework applied to data from 30 countries across diverse income groups. We use WHO COVID-19 surveillance data on new cases and deaths, vaccination data from the Oxford COVID-19 Government Response Tracker, infodemic data (volume of public conversations and social media content) from the WHO EARS platform, and Google Trends data to represent information demand. Our findings show that new deaths are the strongest predictor of the infodemic, measured as new document production including social media content and public conversations, and that the epidemic burden in neighbouring countries appears to have a greater impact on document production than the domestic one. Building on these results, we propose a taxonomy that highlights country-specific discrepancies between the evolution of the infodemic and the epidemic. Further, an analysis of the temporal evolution of the relationship between the two phenomena quantifies how much the discussions around vaccine rollouts may have shaped the development of the infodemic. The insights from our quantitative model contribute to advancing infodemic research, highlighting the importance of a holistic approach integrating both online and offline dimensions.
format Preprint
id arxiv_https___arxiv_org_abs_2501_19016
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Modelling Infodemics on a Global Scale: A 30 Countries Study using Epidemiological and Social Listening Data
Loru, Edoardo
Delmastro, Marco
Gesualdo, Francesco
Cinelli, Matteo
Social and Information Networks
Physics and Society
Infodemics are a threat to public health, arising from multiple interacting phenomena occurring both online and offline. The continuous feedback loops between the digital information ecosystem and offline contingencies make infodemics particularly challenging to define operationally, measure, and eventually model in quantitative terms. In this study, we present evidence of the effect of various epidemic-related variables on the dynamics of infodemics, using a robust modelling framework applied to data from 30 countries across diverse income groups. We use WHO COVID-19 surveillance data on new cases and deaths, vaccination data from the Oxford COVID-19 Government Response Tracker, infodemic data (volume of public conversations and social media content) from the WHO EARS platform, and Google Trends data to represent information demand. Our findings show that new deaths are the strongest predictor of the infodemic, measured as new document production including social media content and public conversations, and that the epidemic burden in neighbouring countries appears to have a greater impact on document production than the domestic one. Building on these results, we propose a taxonomy that highlights country-specific discrepancies between the evolution of the infodemic and the epidemic. Further, an analysis of the temporal evolution of the relationship between the two phenomena quantifies how much the discussions around vaccine rollouts may have shaped the development of the infodemic. The insights from our quantitative model contribute to advancing infodemic research, highlighting the importance of a holistic approach integrating both online and offline dimensions.
title Modelling Infodemics on a Global Scale: A 30 Countries Study using Epidemiological and Social Listening Data
topic Social and Information Networks
Physics and Society
url https://arxiv.org/abs/2501.19016