Naslov
Semi-Local Integration Measure of Node Importance

Autori
Ban Kirigin, Tajana ; Bujačić Babić, Sanda ; Perak, Benedikt

Izvornik
Mathematics (2227-7390) 10 (2022), 3; 1-16

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

Ključne riječi
centrality measure ; node importance ; complex networks ; applications of graph data processing ; lexical graph analysis ; sentiment analysis

Sažetak
Numerous centrality measures have been introduced as tools to determine the import ance of nodes in complex networks, reflecting various network properties, including connectivity, survivability, and robustness. In this paper, we introduce Semi- Local Integration (SLI), a node centrality measure for undirected and weighted graphs that takes into account the coherence of the locally connected subnetwork and evaluates the integration of nodes within their neighbourhood. We illustrate SLI node importance differentiation among nodes in lexical networks and demonstrate its potential in natural language processing (NLP). In the NLP task of sense identification and sense structure analysis, the SLI centrality measure evaluates node integration and provides the necessary local resolution by differentiating the importance of nodes to a greater extent than standard centrality measures. This provides the relevant topological information about different subnetworks based on relatively local information, revealing the more complex sense structure. In addition, we show how the SLI measure can improve the results of sentiment analysis. The SLI measure has the potential to be used in various types of complex networks in different research areas.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo, Filologija

Napomena
This article belongs to the Special Issue New
Trends in Graph and Complexity Based Data Analysis
and Processing

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