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NetLogo User Community Models

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[screen shot]

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If clicking does not initiate a download, try right clicking or control clicking and choosing "Save" or "Download".(The run link is disabled for this model because it was made in a version prior to NetLogo 6.0, which NetLogo Web requires.)

WHAT IS IT?

This is a replication of Robert Axelrod's model of cultural dissemination, as presented in "The Dissemination of Culture: A Model with Local Convergence and Global Polarization".

HOW IT WORKS

Patches are assigned a list of num-features integers which can each take on one of num-traits values. Each tag is called a feature, while it's value is called the trait.

The links in the view represent walls between patches where solid black walls mean there is no cultural similarity, and white walls mean the neighbors have the same culture.

The order of actions is as follows:
1) At random, pick a site to be active, and pick one of it's neighbors
2) With probability equal to their cultural similarity, these sites interact. The active site replaces one of the features on which they differ (if any) with the corresponding trait of the neighbor.

The model ends when no further interactions can take place.

HOW TO USE IT

Setup assigns the patches random culture based on the num-features and num-traits sliders, and updates the walls between them.

The plot "Connected Regions" has 2 pens. The black pen tracks the number of clusters of culturally identical patches, while the red pen tracks the size of the largest cluster. This is a time consuming algorithm for larger scale models, so the interval between updates is controlled by the sample-interval slider.

THINGS TO NOTICE

Q1) Try setting num-features to 5 and num-traits to 10. Under these settings, a typical culture list might be [9 6 0 3 4]. Run the model. How do the plots vary over time? Are changes gradual, or sudden?

Try running the model a few times. What different features can you see under these settings?

Q2) Try increasing num-traits to 15 and then to 20. How does this affect the final picture? Can you explain this?

Q3) With num-traits set at 20, try increasing num-features to 10. What happens now? More features means there is even more variety in culture, so the results may be surprising. What aspect of the model causes this behavior?

A1) These are the settings Axelrod uses in the paper referenced. Often, under these settings we find the culture becomes entirely uniform, and no more walls exist. The switch between generally separate cultures, and a large, connected cluster happens suddenly, where the number of clusters drops and the size of the largest cluster increases steeply.

Sometimes small islands form, and even small clusters isolated from the larger cluster by dramatic cultural differences.

A2) Increasing num-traits to 15 tends to mean the end result is several smaller clusters, through the majority of patches become connected. Further increase to 20 however tends to result in many small clusters, where the largest often occupies less than half of the total space.

A3) Though it may seem counter-intuitive, increasing num-features will tend to result in a larger cluster, and fewer islands. This is because with so many different features, the likelihood of neighbors having nothing in common is small compared with fewer features.

CREDITS AND REFERENCES

Robert Axelrod, "The Dissemination of Culture: A Model with Local Convergence and Global Polarization"
Philip Ball - "Critical Mass"

Any suggestions or questions? e-mail: isw3@le.ac.uk

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