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Home / News

Infectious notions: Applying disease dynamics to ideas

January 2, 2014

When Ben Althouse and Laurent Hebert- Dufresne attended SFI’s 2012 Complex Systems Summer School, they began a productive collaboration, developing a model of influenza resistance to antiviral medications. Later, working with SFI Research Fellow Simon DeDeo, the team applied the contagion model to social dynamics.

“It turns out the models are equally applicable to both systems,” explains Althouse, who recently joined SFI as an Omidyar Fellow.

In the biological case, when someone is treated with antivirals, there’s a chance the viral strain will develop a mutation that makes the antiviral ineffective. The infected person then can have two strains: susceptible and resistant.

In the world of ideas, a person being aware of two complementary or conflicting thoughts simultaneously can result in the ideas boosting each other, or one notion replacing the other. As ideas spread through a population, this phenomenon is repeated, each idea spreading and lingering at various speeds.

Idea modeling breeds its own set of complexities distinct from disease modeling; for example, one can harbor dozens of ideas rather than a strain or two of a pathogen.

A recent SFI working group on the topic, From Coinfection to Cultural Dissonance: New Challenges for Biological and Cultural Evolution, involving the three researchers ran for a month.

They looked to perhaps the best high-volume, publicly available, and massively interconnect- ed contemporary network to develop and test its idea models: Twitter. They sampled one percent of all tweets from Twitter users globally for over a year. The amount of data is staggering: a single 30-minute interval can yield 75,000 samples.

“Twitter is vast,” says Althouse. “There are a lot of ideas bouncing around, a lot of memes, ideas that come up quickly, hang around, then go away, so it’s a good place to look at the replacement of one idea with another.”

Following a good deal of brainstorming about the best ways to apply epidemiological mod- els to memes, the group is now running simu- lations of how contagious ideas spread. 





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