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Shortest path-based centrality metrics in attributed graphs with node-individual context constraints

Title data

Schönfeld, Mirco ; Pfeffer, Jürgen:
Shortest path-based centrality metrics in attributed graphs with node-individual context constraints.
In: Social Networks. (2 November 2021) .
ISSN 0378-8733
DOI: https://doi.org/10.1016/j.socnet.2021.10.004

Project information

Project title:
Project's official titleProject's id
Africa Multiple Cluster of Excellence at the University of BayreuthEXC 2052/1 – 390713894

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

Centrality measurements are a well-known method to assess the importance of actors in networks. They are easy to obtain and provide a versatile interpretability adaptable to the meaning of nodes and edges. The current centrality measurements use structural information alone. In real-world situations, however, actors and the connections between them are subject to contextual settings and can be significantly influenced by these settings. In fact, such real-world observations are often modeled using attributed networks in which contextual information can be associated as attributes to nodes and edges. However, this information is disregarded when evaluating the importance of actors in terms of network centrality measurements. Hence, this paper proposes a method for obtaining shortest path-based centrality measurements for attributed networks that exploit attribute information on nodes for shortest path calculations. We add abstracts of scientific publications to a co-publishing network and use topic models to create node-individual context constraints for shortest path calculations. This creates additional analytic opportunities and can aid in gaining a detailed understanding of complex social networks.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Attributed network; Betweenness centrality; Closeness centrality; Contextual embeddedness
Institutions of the University: Faculties > Faculty of Languages and Literature
Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung
Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 17 Nov 2021 09:44
Last Modified: 17 Nov 2021 09:44
URI: https://eref.uni-bayreuth.de/id/eprint/67656