Research into what makes content go viral on public platforms reveals some surprising patterns. Rather than hostility driving engagement, solidarity-based content performs dramatically better in certain contexts, while TikTok's algorithm has fundamentally changed who gets to participate in viral moments.
Four years ago, the conventional wisdom about viral content was simple: anger and outrage were the fuel. That idea came from solid research showing that divisive posts often go viral on US social media. But newer studies suggest the picture is more complicated than that.
The solidarity surprise
A team of psychologists at the University of Cambridge decided to test that hostility thesis in a very different context. They analyzed 1.6 million posts from Ukrainian news outlets on Facebook and Twitter, covering seven months before and six months after Russia's invasion in February 2022.
What they found flipped the old script. Posts expressing Ukrainian ingroup solidarity saw a 92% engagement boost on Facebook and a 68% boost on Twitter after the invasion, compared to before. People were sharing content that brought them together, not content that tore the other side down.
Now here is where it gets really interesting. Outgroup hostility posts directed at Russia barely moved the needle. They picked up just an extra 1% engagement on Facebook after the invasion began, with no meaningful change on Twitter at all.
So why does this matter? It suggests that virality is not a fixed formula. The same mechanism that drives sharing in one cultural moment can fall flat in another. Solidarity, not rage, was the real engine in this case.
Who actually creates viral content
The other big question in the virality conversation is about barriers to entry. Who gets to be a viral creator, and who stays a passive consumer?
A Penn State study tackled this by looking at political content on TikTok. Researchers analyzed nearly 2 million political videos across 11,546 TikTok accounts. They compared creator behavior on TikTok versus YouTube, and the gap was enormous.
About 78% of viewers who commented on political TikToks had also uploaded videos to the platform. On YouTube, that number was just 18%. That is a staggering difference in participation rates.
The algorithm as gatekeeper
TikTok's design plays a huge role here. The platform's mobile-only interface and recommendation algorithm make content creation and virality particularly easy. You do not need a following to get seen. The algorithm decides what surfaces.
TikTok users also spend an average of 96 minutes per day on the platform, the most total time of any social media company in the United States. More time on a platform where anyone can go viral means more people actually try.
The result is a much lower barrier between watching and creating. When the algorithm can put anyone in front of millions, commenting feels less like shouting into a void and more like a stepping stone.
What this tells us about the attention economy
These two studies, taken together, paint a picture of virality that is shifting. The old playbook said: make people angry at an outgroup, and they will share. The new evidence says it depends entirely on context, and that the platform's architecture determines who even gets to play.
Lower barriers to creation on TikTok mean more voices in the viral mix. And the Cambridge research shows that when the stakes are real, people gravitate toward content that builds community rather than content that attacks.
The question that remains is how this plays out as platforms continue to evolve. If algorithms keep flattening the gap between consumer and creator, and if solidarity consistently outperforms hostility in high-stakes moments, what does that mean for the next wave of viral content? What would you rather see filling your feed: content that unites people, or content that pits them against each other?
Comments