Behavioural Bytes Archives
In a world where false information spreads faster than ever, the parallels between viral contagion and the dissemination of misinformation are striking. Recent studies use epidemiological models — the same tools employed to track and predict disease outbreaks — to map how misinformation infects social networks.
In South Africa, where over 70% of people rely on social media for news, we’ve seen this play out in real time.
Take the recent panic around social grants: misinformation amplified uncertainty for millions of vulnerable citizens, showing how false narratives can create ripple effects through society.
Misinformation can behave like a simple contagion, infecting instantly, or like a complex contagion, requiring repeated exposure to take hold.
“Superspreaders” on social media act like patient zero, amplifying false narratives to millions.
Just as vaccination builds immunity to disease, psychological inoculation (or prebunking) can “immunise” individuals by exposing them to weakened doses of false narratives, paired with factual corrections.
• Cognitive shortcuts: Emotionally charged or repeated information sticks more easily, making misinformation hard to resist.
• Confirmation bias: People seek evidence to reinforce their beliefs, even if flawed.
• Social proof: Seeing others believe misinformation creates an echo chamber, reinforcing credibility.
• Friction prompts like “Are you sure this is accurate?” to slow down sharing.
• Gamified prebunking techniques to make critical thinking engaging and memorable.
• Harnessing trusted voices — like community leaders — to amplify accurate narratives, much like health campaigns.
Epidemiological models allow us to test and predict these interventions before rolling them out. They could help us tackle the unique challenges of misinformation in South Africa and beyond—proactively stopping its spread.
With trust in public systems and social cohesion at stake, the question isn’t just “How do we fight misinformation?” but “How do we prevent it from spreading in the first place?”
What role do you think behavioural insights and predictive modelling can play in this fight? Let’s discuss.
