| 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_by_hierarchy(.data)
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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