A combined approach for evaluating papers, authors and scientific journals

An integrated model for ranking scientific publications together with
authors and journals recently presented in [Bini, Del Corso, Romani,
ETNA 2008]
is closely analyzed. The model, which relies on certain adjacency
matrices $H,K$ and $F$ obtained from the relations of citation,
authorship and publication, provides the ranking by means of the
Perron vector of a stochastic matrix obtained by combining $H,K$ and
$F$. Some perturbation theorems concerning the Perron vector
previously introduced by the authors
are extended to more general cases and a counterexample to a property previously
addressed by the authors
is presented. The theoretical results confirm the
consistency and effectiveness of our model. Some paradigmatic
examples are reported together with some results obtained on a real
set of data.