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
Association for Computing Machinery
Sun, Jun
cbc6b83e-3571-4f6a-b77d-51a8a20ac839
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Karimi, Fariba
5e3871f3-6549-4ce0-9d09-df05b6951b10
15 May 2018
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.
Association for Computing Machinery.
.
(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, BelleVUe Building, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands, 2018-05-27 - 2018-05-30
Identifiers
Local EPrints ID: 421063
URI: http://eprints.soton.ac.uk/id/eprint/421063
PURE UUID: f5e8ea4e-4b11-4c84-ac29-1a222725d26d
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Date deposited: 22 May 2018 16:30
Last modified: 16 Mar 2024 04:22
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Author:
Jun Sun
Author:
Steffen Staab
Author:
Fariba Karimi
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