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Decay of relevance in exponentially growing networks

Decay of relevance in exponentially growing networks
Decay of relevance in exponentially growing networks
We propose a new preferential attachment-based network growth model in order to explain two properties of growing networks: (1) the power-law growth of node degrees and (2) the decay of node relevance. In preferential attachment models, the ability of a node to acquire links is affected by its degree, its fitness, as well as its relevance which typically decays over time. After a review of existing models, we argue that they cannot explain the above-mentioned two properties (1) and (2) at the same time. We have found that apart from being empirically observed in many systems, the exponential growth of the network size over time is the key to sustain the power-law growth of node degrees when node relevance decays. We therefore make a clear distinction between the event time and the physical time in our model, and show that under the assumption that the relevance of a node decays with its age τ, there exists an analytical solution of the decay function f_R with the form f_R(τ) = ?^(τ1). Other properties of real networks such as power-law alike degree distributions can still be preserved, as supported by our experiments. This makes our model useful in explaining and analysing many real systems such as citation networks.
343-351
ACM
Sun, Jun
cbc6b83e-3571-4f6a-b77d-51a8a20ac839
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Karimi, Fariba
5e3871f3-6549-4ce0-9d09-df05b6951b10
Sun, Jun
cbc6b83e-3571-4f6a-b77d-51a8a20ac839
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Karimi, Fariba
5e3871f3-6549-4ce0-9d09-df05b6951b10

Sun, Jun, Staab, Steffen and Karimi, Fariba (2018) Decay of relevance in exponentially growing networks. In WebSci '18 Proceedings of the 10th ACM Conference on Web Science. ACM. pp. 343-351. (doi:10.1145/3201064.3201084).

Record type: Conference or Workshop Item (Paper)

Abstract

We propose a new preferential attachment-based network growth model in order to explain two properties of growing networks: (1) the power-law growth of node degrees and (2) the decay of node relevance. In preferential attachment models, the ability of a node to acquire links is affected by its degree, its fitness, as well as its relevance which typically decays over time. After a review of existing models, we argue that they cannot explain the above-mentioned two properties (1) and (2) at the same time. We have found that apart from being empirically observed in many systems, the exponential growth of the network size over time is the key to sustain the power-law growth of node degrees when node relevance decays. We therefore make a clear distinction between the event time and the physical time in our model, and show that under the assumption that the relevance of a node decays with its age τ, there exists an analytical solution of the decay function f_R with the form f_R(τ) = ?^(τ1). Other properties of real networks such as power-law alike degree distributions can still be preserved, as supported by our experiments. This makes our model useful in explaining and analysing many real systems such as citation networks.

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More information

Published date: 15 May 2018
Venue - Dates: 10th ACM Annual Conference on Web Science: Web Science 2018, Amsterdam, Netherlands, 2018-05-27 - 2018-05-30

Identifiers

Local EPrints ID: 421063
URI: https://eprints.soton.ac.uk/id/eprint/421063
PURE UUID: f5e8ea4e-4b11-4c84-ac29-1a222725d26d
ORCID for Steffen Staab: ORCID iD orcid.org/0000-0002-0780-4154

Catalogue record

Date deposited: 22 May 2018 16:30
Last modified: 19 Jul 2018 00:28

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Contributors

Author: Jun Sun
Author: Steffen Staab ORCID iD
Author: Fariba Karimi

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