Open AccessStudying the COVID-19 infodemic at scale
Author(s) -
Anatoliy Gruzd,
Manlio De Domenico,
Pier Luigi Sacco,
Sylvie Briand
Publication year - 2021
Publication title -
big data and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.244
H-Index - 37
ISSN - 2053-9517
DOI - 10.1177/20539517211021115
Subject(s) - big data , covid-19 , data science , theme (computing) , social media , scale (ratio) , computer science , computational sociology , sociology , medicine , data mining , world wide web , physics , disease , pathology , virology , quantum mechanics , outbreak , infectious disease (medical specialty)
This special theme issue of Big Data & Society presents leading-edge, interdisciplinary research that focuses on examining how health-related (mis-)information is circulating on social media. In particular, we are focusing on how computational and Big Data approaches can help to provide a better understanding of the ongoing COVID-19 infodemic (overexposure to both accurate and misleading information on a health topic) and to develop effective strategies to combat it.