Can Mathematics Explain Mob Behavior? : Physicist Applies Fluid Mechanics to Study of How Crowds React

Sir Isaac Newton was intrigued by the dynamics of the way things moved.

At the heart of his work, which resulted in the laws of motion, was a mathematical explanation for just about everything from the revolution of planets to the movement of liquids and other substances that flow.

A theoretical physicist at the Los Alamos National Laboratory in New Mexico is taking hundreds of years of fluid mechanics study a step further.

Frank Harlow thinks that not only can the basic equations of fluid mechanics describe the minute world of molecules but may also provide some insights into human behavior. Particularly, the dynamics of a mob.

Far fetched?

“No, not really,” said Harlow from his laboratory at the massive research complex.

He strongly believes that the flow of water from a tap and the flow of an angry mob into a street have more in common than a metaphoric relationship. And to illustrate that hypothesis, he has developed a computer program to bear out his ideas.

Excitement Spreads

“The computer model shows how excitement can spread through a crowd,” he said. “The model for mob behavior actually is a modification of one originally used to simulate turbulence in liquids.”

Violent eddies, swirling against a main current of water, for example, do so because billions of molecules have become agitated and contribute to the swirling fury of the whirlpool.

The greater that agitation, the more violent the eddy.

“The whirlpools are more complex than the individual molecules that make them up,” said Harlow, who also noted that even though motion at the molecular level is among individual molecules, they all respond to the same stimuli.

“Have you ever heard the word sale mentioned over a loudspeaker in a department store and then noticed the rush of people?” Harlow asked. “People who weren’t interacting suddenly are.”

“Humans are more complex than molecules,” he said, “but the word sale provided the impetus for forceful movement,” motion that lends itself to quantification and computer study.

The physicist said the computer programs cannot predict what a crowd will do but can produce the most probable consequences of an event.

Mob Formation Traced

Harlow’s computer modeling studies, which have attracted the attention of military strategists in the Pentagon and police department SWAT teams across the country, show that mobs develop in rapid, but definable stages.

People most susceptible and closest to a source of excitement are usually the first ones attracted to a mob, just as molecules of water closest to a source of heat are the first to become active, he said.

As the mob begins to take shape, attraction to the group appears to spread out as if in concentric circles from the closest to farthest groups of people. Within seconds, people who had nothing in common become interacting members of a mob.

He said the impetus for mob-like behavior can be precipitated by fear, anger, the haranguing and encouragement of a charismatic speaker or some promise of reward.

“If you are walking down the street and see a big crowd of people and suddenly someone says, ‘There are big piles of money over there, lets go,’ your heart will start to beat faster. Your adrenaline will start to flow; you’ll move with the group and that means you’ve caught the infectiousness of the mob.”

Other Applications

Harlow believes his computer modeling eventually will have applications for studying other cause-and-effect sequences in the animal world, such as schools of fish that swiftly change direction or the movement of packs of dogs.

“I’ve always been intrigued by what we can do with the same mathematics insofar as the functions apply to other collective sets of things or entities such as a school of fish or a flock of birds.

“All of this relates to fluid mechanics in the following ways: if you have air, gas or water made up of a lot of molecules, they can be in a turbulent state and bounce around among each other.

“But they also have very powerful collective behavior,” he said referring to the similarity to a mob.