Millions of people flock to YouTube to watch videos of lions, tigers and bears, but a new study reveals that this digital enthusiasm rarely translates into real-world action.
Researchers from the University of Michigan analysed nearly 25,000 comments posted on wildlife videos and found that just 2 per cent contained a “call to action” to support conservation efforts.
The study, published in the journal Communications Sustainability, highlights a significant disconnect between the popularity of nature content and the public’s willingness to engage in its preservation.
“Our results basically show that people like to watch videos of zoos and safaris and that they appreciate the aesthetics and majesty of certain animals,” says Derek Van Berkel, an associate professor at the U-M School for Environment and Sustainability. “But there really wasn’t much of a nuanced conversation about conservation.”
A missed opportunity
The researchers analysed the YouTube “8M dataset“, filtering for videos classified as wildlife that contained English-language comments. They focused on footage from zoos, safaris and hunting, using both human analysis and machine learning to categorise the sentiment of the comments.
While viewers frequently expressed appreciation for or concern about the animals, concrete steps — such as urging others to contact elected officials or support conservation charities — were virtually nonexistent.
“I was hoping there might be more,” says Van Berkel. “I thought it might be bigger than two per cent.”
However, the team views this gap as a “huge potential” rather than a failure. The study noted a distinct absence of conservation groups and influencers in the comment sections, suggesting that environmental organisations are missing a prime opportunity to steer the conversation.
“The flip side of this is we can and should do better at messaging,” says co-author Neil Carter. “There’s tremendous untapped potential for conservation messaging to be improved.”
Needle in a haystack
Training a computer to find these calls to action proved difficult simply because there were so few examples to learn from.
“If the label you’re looking for happens far less often than the others, that problem is really hard. You’re looking for a needle in a haystack,” explains co-author Sabina Tomkins, an assistant professor at the U-M School of Information.
