EI | R Documentation |
The EI-Index is the division of the surplus count intra-group edges over inter-group edges,
divided by total count of all edges.
This implementation uses the intra-group and inter-group density instead
of edge counts, when rescale
is set to TRUE
(default). The EI-Index is calculated for
the whole network and for subgroups. Alternatively, the EI index can be employed as a measurement
for egos tendency to homo-/heterophily - use comp_ei()
.
for that variant of the EI-Index.
EI(object, alt.attr, include.ego = FALSE, ego.attr = alt.attr, rescale = TRUE)
object |
An |
alt.attr |
|
include.ego |
|
ego.attr |
|
rescale |
|
The
whole network EI is a metric indicating the tendency of a network to be
clustered by the categories of a given factor variable (alt.attr
). The EI value of a
group describes the tendency of that group within a network to be connected
(if between 0 and 1) or not connected (if between -1 and 0)
to other groups. Differing group sizes can lead to a distortion of EI values
i.e. the ability of a big group A to form relationships to much smaller group B
is limited by the size of B. Even when all possible edges between A and B exist,
the EI value for group A might still be negative, classifying it as homophile.
The re-scaled
EI-Index values provided by this implementation substitutes absolute
edge counts by inter- and intra-group edge densities in order to avoid the
distortion of the EI-Index values. These values express the extend of homo- or heterophily
of the network and its subgroups, as made possible by subgroup sizes.
Returns tibble
with the following columns:
ego ID (".egoID")
network EI-Index ("ei")
subgroup EI-Index values (named by value levels of alt.attr
/ego.attr
)
Krackhardt, D., Stern, R.N., 1988. Informal networks and organizational crises: an experimental simulation. Social Psychology Quarterly 51 (2), 123-140.
Everett, M. G., & Borgatti, S. P. (2012). Categorical attribute based centrality: E-I and G-F centrality. Social Networks, 34(4), 562-569.
comp_ei()
, for an ego level homophily measure.
data("egor32")
EI(egor32, "sex")
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