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The authority scores of the vertices are defined as the principal
eigenvector of
authority_score(graph, scale = TRUE, weights = NULL, options = arpack_defaults)
The input graph.
Logical scalar, whether to scale the result to have a maximum score of one. If no scaling is used then the result vector has unit length in the Euclidean norm.
Optional positive weight vector for calculating weighted
scores. If the graph has a weight
edge attribute, then this is used
by default.
This function interprets edge weights as connection strengths. In the
random surfer model, an edge with a larger weight is more likely to be
selected by the surfer.
A named list, to override some ARPACK options. See
arpack
for details.
A named list with members:
The authority/hub scores of the vertices.
The corresponding eigenvalue of the calculated principal eigenvector.
Some information about the ARPACK computation, it has
the same members as the options
member returned
by arpack
, see that for documentation.
For undirected matrices the adjacency matrix is symmetric and the
authority scores are the same as hub scores, see
hub_score
.
J. Kleinberg. Authoritative sources in a hyperlinked environment. Proc. 9th ACM-SIAM Symposium on Discrete Algorithms, 1998. Extended version in Journal of the ACM 46(1999). Also appears as IBM Research Report RJ 10076, May 1997.
hub_score
, eigen_centrality
for
eigenvector centrality, page_rank
for the Page Rank
scores. arpack
for the underlining machinery of the
computation.
# NOT RUN {
## An in-star
g <- make_star(10)
hub_score(g)$vector
authority_score(g)$vector
## A ring
g2 <- make_ring(10)
hub_score(g2)$vector
authority_score(g2)$vector
# }
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