member_diffusion {manynet} | R Documentation |
Membership of nodes in a diffusion
Description
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
Usage
node_in_adopter(.data)
Arguments
.data |
An object of a manynet-consistent class:
|
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
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)