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Voting - Network Knowledge

by Nate Wong (Submitted: 06/02/2009 )

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(You can also run this model in your browser, but we don't recommend it; details here.)

WHAT IS IT?

This model attempts to show the effects of tacit strategic voting by separating the action of voting into two steps: information gathering and vote choice.

HOW IT WORKS

Each patch represents a voter. Initially, patches are randomly assigned an ideal stance in the 2D issue space and are randomly given information about the platform of a single candidate.

Ideal stances and candidate platforms are stationary throughout each run of the model.
By default, patches vote for the only candidate they are aware of. As the model runs, patches acquire information selectively based on information of the neighboring 8 patches and update their preferences. For each patch, if sufficiently many neighbors know the platform of a candidate, then the patch will become informed about that platform.

In this model, there is no explicit strategic voting. Patches always vote for the nearest known candidate in the issue space.

HOW TO USE IT

Click the "setup" button. Patches will update their color based on their randomly assigned candidate information.

Click the "go" button. Each tick, patches will update their information and consequently their color.

The parameters "A-xcor", "A-ycor", "B-xcor", "B-ycor", "C-xcor", "C-ycor" refer to the platforms of the three candidates {A,B,C} in the 2D issue space.

The parameters "neighbors-needed-X" refer to the number of neighboring patches that must know the platform of "candidate X" for there to be a transmission of information.

The monitors represent the percent of the population that are currently voting for each candidate and that currently know the platform for each candidate.

The graphs record the change in vote totals for each candidate.

THINGS TO NOTICE

Watch how long it takes for the model to settle down with respect to the information constraint parameters.

Notice which candidate benefits from an information constraint placed on a single candidate or on all three candidates.

THINGS TO TRY

Compare the effects of the information constraint in this model to that in the
"Voting - Network Vote Choie" model, and see the difference in overal patch knoweldge.

EXTENDING THE MODEL

Adding in explicit strategic voting would make the model even more dynamic.

RELATED MODELS

Voting (the intial inspiration for the model)

Voting - Network Vote Choice (similar model except learning occurs based on neighboring patches' vote choice rather than knowledge)

CREDITS AND REFERENCES

Wong, N & Wilensky, U. (2009). NetLogo Voting Network Knowledge model. http://ccl.northwestern.edu/netlogo/models/community/Voting - Network Knolwedge. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Wong, N. & Wilensky, U. (2009). NetLogo Voting Network Vote Choice model. http://ccl.northwestern.edu/netlogo/models/community/Voting - Network Vote Choice. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Wilensky, U. (1998). NetLogo Voting model. http://ccl.northwestern.edu/netlogo/models/Voting. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

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