A Generalized Notion of Time for Modeling Temporal Networks

Kueffner, Konstantin; Strembeck, Mark

doi:10.5220/0007764000930100

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2021

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“…Thereby, our approach allows for considering nondeterministic and incomplete data when analyzing temporal networks-two issues that often appear when dealing with real-world data, such as data extracted from online social networks. This paper is a corrected and significantly extended version of Kueffner & Strembeck (2019).…”

Section: Introductionmentioning

confidence: 99%

Toward a generalized notion of discrete time for modeling temporal networks

Kueffner

Strembeck

2021

Net Sci

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Many real-world networks, including social networks and computer networks for example, are temporal networks. This means that the vertices and edges change over time. However, most approaches for modeling and analyzing temporal networks do not explicitly discuss the underlying notion of time. In this paper, we therefore introduce a generalized notion of discrete time for modeling temporal networks. Our approach also allows for considering nondeterministic time and incomplete data, two issues that are often found when analyzing datasets extracted from online social networks, for example. In order to demonstrate the consequences of our generalized notion of time, we also discuss the implications for the computation of (shortest) temporal paths in temporal networks. In addition, we implemented an R-package that provides programming support for all concepts discussed in this paper. The R-package is publicly available for download.

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Section: Introductionmentioning

confidence: 99%