How social media prevent tipping points for positive change
Tipping points are a frequently quoted tool for social change and climate protection among activists and supporters. The idea that it takes 25% of supporters of a plan to create change is popular. But does this conclusion hold up under the pressure of social media?
A frequently quoted study concluded that 25% of people can cause a tipping point. It originates from research conducted by Damon Centola and his colleagues at the University of Pennsylvania. Their study, “Experimental Evidence for Tipping Points in Social Convention,” was published in Science in 2018.
In this experimental study, Centola and his team found that when a committed minority reached 25% of the total group, there was an abrupt change in group dynamics, leading to the majority’s rapid adoption of a new norm. This finding challenged previous speculations that tipping points could range anywhere between 10% and 40%.
The researchers tested their theory by creating groups of 20 participants who were given financial incentives to agree on a linguistic norm. They then introduced a coalition of activists of varying sizes to push for a change in the established norm. The study revealed that:
- Minority groups below 25% failed to change the norm.
- When the committed minority reached 25%, the majority quickly adopted the new norm.
- In some cases, a single person made the difference between success and failure.
The game changed
However, at the time of the research, social media was less influential and much less polarized than today, requiring a critical review of that conclusion.
Centola mentions that social networks play a crucial role in reaching the 25% tipping point for social change, supporting the spread of ideas, behaviors, and norms. However, participants in the experiment could interact transparently and on equal terms—that is, unfiltered, in direct interaction with each other, real human beings. But then someone sent in the bots.
In the original research, the process was supposed to work like this:
- Complex Contagion: Unlike simple contagions (e.g., information or disease spread), social change typically spreads as a complex contagion, requiring multiple sources of social reinforcement to induce adoption. This means that individuals are more likely to adopt a new behavior or idea when they see it reinforced by multiple connections in their social network.
- Social Reinforcement: As ideas spread through networks, they gain credibility and momentum. When people see their peers adopting a new behavior or supporting a cause, they are more likely to join in, creating a cascading effect.
- Network Structure: The structure of social networks can significantly impact the spread of ideas. Highly connected networks create more opportunities for interaction and exposure to new ideas, potentially accelerating the path to the tipping point.
And social media platforms were supposed to work like this:
- Rapid Information Spread: Digital networks allow for quick dissemination of ideas, potentially accelerating the time it takes to reach the critical mass.
- Visibility of Support: Social media makes it easier for people to see how many others support an idea, which can encourage more to join when the numbers approach the tipping point.
- Cross-Platform Influence: The interconnected nature of various social media platforms can amplify messages across different networks, potentially reaching diverse segments of the population more quickly.
New challenges for tipping points
While social networks were considered powerful tools for reaching tipping points, there were important limiting factors at the time of the research. Social media algorithms already then could create echo chambers, potentially limiting the spread of ideas beyond like-minded groups.
And the same dynamics that allow for positive social change can be exploited by actors seeking to influence public opinion for less benevolent purposes. Centola already mentioned that.
But then came the bots. By now, their use has become an essential barrier to positive change. They obstruct the 25% rule for positive change by rigging the system and consistently oppose opinions that support the protection of the climate and a sustainable transition. To every human message, they can post a random number of messages that oppose the initial message. These messages are formatted in ways that create maximum interaction. Like that, human messages can easily be prevented from reaching a critical threshold, while the bots create an opposing tipping point for the purposes of their creators.
Nonetheless, the study from Damon Cetola has not yet been replicated, nor has any evidence for its validity occurred in real life. Yes, there are indications of critical tipping points. And tipping points do occur. But it seems impossible to pinpoint them at a precise percentage of a population. On the other hand, the working of bots presents a solid concept to prevent positive social tipping points from happening, whatever the threshold might be. They simply outnumber their opponents. And with the recent abolishment of fact-checking on main social media, they are given a free ride. Under His Eye.
Peet Osta
Also published on iNSnet
