Covid 19: Mapping changing sentiment in tweets

Using machine learning, researchers analysed 30 million English language tweets from across the world to track the changing global sentiment as the Covid-19 pandemic spread. Lead author of the study, professor May Lwin at Nanyang Technological University in Singapore explains how machine learning found that sentiments of fear in the early months of the pandemic are now outnumbered by anger and hope.

Researcher Aretha Mare, from The Next Einstein Forum in Rwanda says the pandemic has put a renewed focus on home grown African initiatives involving Artificial intelligence. Already some novel approaches to testing and tracing have been developed. These could have global impact.

The pandemic has made weather forecasting less accurate. Aircraft help forecasters gather changes in data such as temperature, humidity and pressure during the course of a flight. Environmental researcher, Ying Chen explains how fewer commercial flights during the pandemic have affected the amount of data gathered by forecasters.

(Image: Getty images)

Producer: Julian Siddle