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Comparing Network Centrality Measures as Tools for Identifying Key Concepts in Complex Networks: A Case of Wikipedia


Matas, Neven; Martinčić-Ipšić, Sanda; Meštrović, Ana
Comparing Network Centrality Measures as Tools for Identifying Key Concepts in Complex Networks: A Case of Wikipedia // Journal of Digital Information Management, 15 (2017), 4; 203-2013 (podatak o recenziji nije dostupan, članak, znanstveni)


Naslov
Comparing Network Centrality Measures as Tools for Identifying Key Concepts in Complex Networks: A Case of Wikipedia

Autori
Matas, Neven ; Martinčić-Ipšić, Sanda ; Meštrović, Ana

Izvornik
Journal of Digital Information Management (0972-7542) 15 (2017), 4; 203-2013

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Complex Networks, Concept Analysis, Keyword Extraction, Network Centralities, Wikipedia

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



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