measure_hierarchy | R Documentation |
These functions, together with net_reciprocity()
, are used jointly to
measure how hierarchical a network is:
net_connectedness()
measures the proportion of dyads in the network
that are reachable to one another,
or the degree to which network is a single component.
net_efficiency()
measures the Krackhardt efficiency score.
net_upperbound()
measures the Krackhardt (least) upper bound score.
net_connectedness(.data)
net_efficiency(.data)
net_upperbound(.data)
.data |
An object of a manynet-consistent class:
|
Krackhardt, David. 1994. Graph theoretical dimensions of informal organizations. In Carley and Prietula (eds) Computational Organizational Theory, Hillsdale, NJ: Lawrence Erlbaum Associates. Pp. 89-111.
Everett, Martin, and David Krackhardt. 2012. “A second look at Krackhardt's graph theoretical dimensions of informal organizations.” Social Networks, 34: 159-163. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.socnet.2011.10.006")}
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_holes
,
measure_periods
,
measure_properties
,
member_diffusion
net_connectedness(ison_networkers)
1 - net_reciprocity(ison_networkers)
net_efficiency(ison_networkers)
net_upperbound(ison_networkers)
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