Gary Mckeown and Noel Sheehy (2006)
Mass Media and Polarisation Processes in the Bounded Confidence Model of Opinion Dynamics
Journal of Artificial Societies and Social Simulation
vol. 9, no. 1
<http://jasss.soc.surrey.ac.uk/9/1/11.html>
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Received: 17-Jun-2005 Accepted: 27-Oct-2005 Published: 31-Jan-2006
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where μ is the convergence parameter (Deffuant et al., 2000). Like the original model all initial opinions are randomly generated across a uniform distribution between 0 and 1 (or later -1 and 1).
Figure 1. Convergence to a Central Opinion. p = 0, d = 0.5, μ = 0.3, n = 100, N = 2500 |
Figure 2. Central Convergence with Isolated Extremes. p = 0, d = 0.25, μ = 0.3, n = 100, N = 2500 |
Figure 3. Opinion in a state of constant change around a Central Opinion. p = 1, d = 0.7, μ = 0.3, n = 100, N = 2500 |
Figure 4. Opinion settles in two extreme groups. p = 1, d = 0.4, μ = 0.3, n = 100, N = 2500 |
Figure 5. Opinion settles at one extreme after a period of persistent opinion exchange. p = 1, d = 0.5, μ = 0.3, n = 100, N = 2500 |
Figure 6. A sequence of screenshots showing two groups of opinion and with gradients of opinion exchange. p = 1, d = 0.5, μ = 0.3, n = 100, N = 2500, Red = 1, Black = 0, one iteration = a single opinion exchange |
Figure 7. Convergence at extremes with Isolated Moderate Opinions. p = 1, d = 0.25, μ = 0.3, n = 100, N = 2500 |
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Figure 8a. Standard Deviations for Threshold and Broadcast Ratio after an average of 1000 iterations per agent |
Figure 8b. Contour graph showing Standard Deviations for Threshold and Broadcast Ratio after an average of 1000 iterations per agent |
Figure 9a. The indicator y for Threshold and Broadcast Ratio after an average of 1000 iterations per agent |
Figure 9b. Contour graph showing the indicator y for Threshold and Broadcast Ratio after an average of 1000 iterations per agent |
Figure 9c. Contour graph showing the indicator y for Threshold and Broadcast Ratio after an average of 10000 iterations per agent |
Figure 10. Single extreme convergence with a broadcast ratio of 1:100 for 10000 iterations. p = 1, d = 1, μ = 0.3, n = 100, N = 2500 |
Figure 11a. Standard Deviations for Threshold and Polarisation after an average of 10000 iterations per agent |
Figure 11b. Contour graph showing Standard Deviations for Threshold and Polarisation after an average of 10000 iterations per agent |
Figure 12. Constant change of central opinions with islands of extremists with homogenous opinions. p = 0.3, d = 0.25, μ = 0.3, n = 100, N = 2500 |
Figure 13. Constant change of central opinions with islands of extremists with homogenous opinions. p = 0.3, d = 0.25, μ = 0.3, n = 100, N = 2500 |
Figure 14a. The indicator y for Threshold and Polarisation after an average of 1000 iterations per agent |
Figure 14b. Contour graph showing the indicator y for Threshold and Polarisation after an average of 1000 iterations per agent |
Figure 15a. The indicator y for Threshold and Polarisation after an average of 10000 iterations per agent |
Figure 15b. Contour graph showing the indicator y for Threshold and Polarisation after an average of 10000 iterations per agent |
Figure 16. Straying from one regime to another. p = 1, d = 0.64, μ = 0.3, n = 100, N = 2500 |
Figure 17a. Standard Deviations for Threshold and Polarisation using a Moore nieghbourhood with 8 neighbours after an average of 1000 iterations per agent |
Figure 17b. Standard Deviations for Threshold and Polarisation using a Moore neighbourhood with 8 neighbours after an average of 1000 iterations per agent |
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