@article{2303,
  author = {Neven Matas, Sanda Martincic-Ipšic, Ana Meštrovic},
  title = {Comparing Network Centrality Measures as Tools for Identifying Key Concepts in Complex Networks: A Case of Wikipedia},
  journal = {Journal of Digital Information Management},
  year = {2017},
  volume = {15},
  number = {4},
  doi = {},
  url = {http://dline.info/fpaper/jdim/v15i4/jdimv15i4_3.pdf},
  abstract = {Network centralities are amongst the most
important measures for tracking and locating crucial nodes
in a network. In this paper, we propose a general approach
for identifying the most suitable centrality measure for
detecting key concepts in a semantic or linguistic network.
We experiment with seven network centrality measures
(degree centrality, betweenness centrality, closeness
centrality, eigenvector centrality, current-flow betweenness
centrality, current-flow closeness centrality and
communicability centrality). For the purpose of evaluation,
we compare the original Wikipedia hyperlink network with
a constructed concept network. The obtained results
indicate that all seven used measures have good potential
for identifying key terms, and that degree centrality
achieves the best score. A good score is also obtained
for current-flow betweenness centrality and current-flow
closeness centrality.},
}