Gisela Redondo-Sama

TL;DR: Analysis of the type of tweets that circulated on Twitter around the COVID-19 outbreak for two days, in order to analyze how false and true information was shared, shows that false information is tweeted more but retweeted less than science-based evidence or fact-checking tweets, while science- based evidence and fact- checking tweets capture more engagement than mere facts.

TL;DR: The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and deliberation contexts promoted in social media overcome false information about health.

TL;DR: The social impact coverage ratio (SICOR) is defined to identify the percentage of tweets and Facebook posts providing information about potential or actual social impact in relation to the total amount of social media data found related to specific research projects.

TL;DR: Comparisons of the type of Tweets and Sina Weibo posts regarding COVID-19 that contain either false or scientific veracious information show that there is more false news published and shared on Twitter than in Sina weibo, at the same time science-based evidence is more shared onTwitter than in Weibo but less than false news.

TL;DR: In this paper, the authors analyzed the immediate responses in social work to vulnerable groups in the first 15 days of the pandemic in Barcelona, one of the most affected areas worldwide by COVID-19.