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DIFFUSION SIMULATION
This program first creates a social network and then simulates the diffusion of an innovation through the network following a combination of the Bass model and a network contagion model. Agents turn red as they adopt the innovation. New adopters are shown as hollow red circles and incumbent adopters as solid red circles. In a Bass model (unlike an S-I-R model) adoption is permanent. Small green numbers show the number of neighbors having adopted. HOW TO USE IT
Press "setup" to create the social network following Barabasi's preferential attachment model. "Wipe" will reset the diffusion process but keep the social network. "Go" and "go-once" simulate the diffusion process.
Adjust the sliders to see how the diffusion reacts to different assumptions.
The "constant effect" is an effect that applies to all agents and has the same effect at all time periods. Substantively it can be taken to reflect things like advertising or government mandates. It is sometimes referred to as a "mass media effect," "a," or "p."
The "endogenous effect" is a non-spatial cumulative advantage effect that applies to all agents but is a function of popularity (including among "strangers"). Substantively it can be taken to reflect things like bestseller lists or search algorithms like PageRank. It is sometimes referred to as an "information cascade," "network externalities," "b," or "q."
The "cohesion effect" is how sensitive an agent is to neighbors. (This is similar to the "endogenous" effect but applies only to neighbors rather than the whole population). It substantively reflects "word of mouth." This effect is sometimes referred to as "network diffusion," "contagion," or "local network externalities."
Note that under some circumstances the "endogenous" and "cohesion" effects behave similarly and both usually produce an "s-curve." In many works (e.g., Bass 1969, Rogers 2003) a model specification that lacks network structure (and thus is similar to the "endogenous effect") is given a substantive interpretation of a "cohesion effect." CREDITS AND REFERENCES
This model was written by Gabriel Rossman of the UCLA Depatment of Sociology. Substantial parts of the code are borrowed from Wilensky's "Preferential Attachment" model.
For additional information:
Abrahamson, Eric and Lori Rosenkopf. 1997. ÒSocial Network Effects on the Extent of Innovation Diffusion: A Computer Simulation.Ó Organization Science 8:289Ð309.
Bass, Frank M. 1969. ÒA New Product Growth for Model Consumer Durables.Ó Management Science 50:1825Ð1832.
DiMaggio, Paul J. and Filiz Garip. 2010. ÒIntergroup Inequality as a Product of Diffusion of Practices with Network Externalities under Conditions of Homophily: Applications to the Digital Divide in the U.S. and Rural/Urban Migration in Thailand.Ó Princeton University Center for the Study of Social Organization Working Paper #2.
Rogers, Everett M. 2003. Diffusion of Innovations. New York: Free Press, 5th edition.
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