member_diffusion function

Membership of nodes in a diffusion

node_in_adopter() classifies membership of nodes into diffusion categories by where on the distribution of adopters they fell. Valente (1995) defines five memberships:

• Early adopter: those with an adoption time less than the average adoption time minus one standard deviation of adoptions times
• Early majority: those with an adoption time between the average adoption time and the average adoption time minus one standard deviation of adoptions times
• Late majority: those with an adoption time between the average adoption time and the average adoption time plus one standard deviation of adoptions times
• Laggard: those with an adoption time greater than the average adoption time plus one standard deviation of adoptions times
• Non-adopter: those without an adoption time, i.e. never adopted

node_in_adopter(diff_model)

Arguments

• diff_model: A valid network diffusion model, as created by as_diffusion() or play_diffusion().

Examples

smeg <- generate_smallworld(15, 0.025)
  smeg_diff <- play_diffusion(smeg, recovery = 0.2)
  # To classify nodes by their position in the adoption curve
  (adopts <- node_in_adopter(smeg_diff))
  summary(adopts)

References

On adopter classes

Valente, Tom W. 1995. Network models of the diffusion of innovations

(2nd ed.). Cresskill N.J.: Hampton Press.

See Also

Other measures: measure_attributes, measure_central_between, measure_central_close, measure_central_degree, measure_central_eigen, measure_closure, measure_cohesion, measure_diffusion_infection, measure_diffusion_net, measure_diffusion_node, measure_features, measure_heterogeneity, measure_hierarchy, measure_holes, measure_periods, measure_properties

Other diffusion: make_play, measure_diffusion_infection, measure_diffusion_net, measure_diffusion_node