  Preliminary report on network based keyword extraction for Croatian is an
unsupervised method for keyword extraction from the complex network. We build
our approach with a new network measure the node selectivity, motivated by the
research of the graph based centrality approaches. The node selectivity is
defined as the average weight distribution on the links of the single node. We
extract nodes (keyword candidates) based on the selectivity value. Furthermore,
we expand extracted nodes to word-tuples ranked with the highest in/out
selectivity values. Selectivity based extraction does not require linguistic
knowledge while it is purely derived from statistical and structural
information en-compassed in the source text which is reflected into the
structure of the network. Obtained sets are evaluated on a manually annotated
keywords: for the set of extracted keyword candidates average F1 score is
24,63%, and average F2 score is 21,19%; for the exacted words-tuples candidates
average F1 score is 25,9% and average F2 score is 24,47%.
