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COMPUTING SCIENCE

Rumours and Errours

Brian Hayes

The Rumor Mill

I was curious to see the rumor models in action, and so I wrote a little program. I set up a population of 1,000 individuals, each of whom could be an ignorant, a spreader or a stifler. Initially there was just one spreader and all the rest were ignorants. At the heart of the program was the following procedure, meant to implement the Daley-Kendall model (the one in which pairs of spreaders annihilate each other):

repeat

    choose X at random from among the spreaders in the population;

    choose Y at random from the entire population;

    if Y is an ignorant

       then make Y a spreader

    else if Y is a spreader

       then make both X and Y stiflers

    else if Y is a stifler

       then make X a stifler

until there are no more spreaders

When all the spreaders are gone, nothing more can change, so the program ends and reports the fraction of the population still oblivious of the rumor. This fraction, designated θ, should be 0.203188. But the result from my program, averaged over a few thousand runs, was 0.28 or 0.29—a considerable discrepancy.

At this point, let me pause to say that my big boo-boo had already been committed. Before reading on, you might want to try debugging my algorithm, or even write a program of your own.





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