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During a health crisis, the first instinct is often to give people information. Governments make announcements. Experts explain what is happening. Health departments share information on television, radio, social media and through communities. The idea seems simple: give people the right information, and they can make better decisions.

But does simply providing more information resolve uncertainty, misinformation or public concern?

My research focuses on infodemics, using artificial intelligence and machine learning to understand how misinformation spreads, identify information voids and analyze the concerns and questions that emerge during a crisis.

In a recent paper, a group of researchers involved in studying infodemics and I examined the system South Africa put in place to understand public concerns and what responses were recommended to address them.

During the COVID pandemic, South Africa's national Department of Health established a technical Risk Communication and Community Engagement working group that used a research approach called social listening to identify what people were saying, asking and worrying about in relation to the pandemic.

To do this, public conversations and feedback were tracked across social media, online news, public WhatsApp streams, call centers and community channels.

Regular social listening reports brought this information together to identify concerns, misinformation, rumors and gaps in understanding. These reports alerted health authorities and partners to emerging concerns and provided recommended actions for addressing them.

The social listening system was structured as a circular process: listen, understand the problem, recommend a response and keep listening.

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