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Self-avoiding pruning random walk on signed network. / Wang, Huijuan; Qu, Cunquan; Jiao, Chongze; Ruszel, Wioletta.

In: New Journal of Physics, Vol. 21, 035001, 2019.

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Wang, Huijuan ; Qu, Cunquan ; Jiao, Chongze ; Ruszel, Wioletta. / Self-avoiding pruning random walk on signed network. In: New Journal of Physics. 2019 ; Vol. 21.

BibTeX

@article{d746dec7c1d84ab894afa9eaaed45c97,
title = "Self-avoiding pruning random walk on signed network",
abstract = "A signed network represents how a set of nodes are connected by two logically contradictory types of links: positive and negative links. In a signed products network, two products can be complementary (purchased together) or substitutable (purchased instead of each other). Such contradictory types of links may play dramatically different roles in the spreading process of information, opinion, behaviour etc. In this work, we propose a self-avoiding pruning (SAP) random walk on a signed network to model e.g. a user's purchase activity on a signed products network. A SAP walk starts at a random node. At each step, the walker moves to a positive neighbour that is randomly selected, the previously visited node is removed and each of its negative neighbours are removed independently with a pruning probability r. We explored both analytically and numerically how signed network topological features influence the key performance of a SAP walk: the evolution of the pruned network resulted from the node removals, the length of a SAP walk and the visiting probability of each node. These findings in signed network models are further verified in two real-world signed networks. Our findings may inspire the design of recommender systems regarding how recommendations and competitions may influence consumers' purchases and products' popularity.",
keywords = "random walk, signed network, self-avoiding walk, OA-Fund TU Delft",
author = "Huijuan Wang and Cunquan Qu and Chongze Jiao and Wioletta Ruszel",
year = "2019",
doi = "10.1088/1367-2630/ab060f",
language = "English",
volume = "21",
journal = "New Journal of Physics",
issn = "1367-2630",
publisher = "IOP Publishing",

}

RIS

TY - JOUR

T1 - Self-avoiding pruning random walk on signed network

AU - Wang, Huijuan

AU - Qu, Cunquan

AU - Jiao, Chongze

AU - Ruszel, Wioletta

PY - 2019

Y1 - 2019

N2 - A signed network represents how a set of nodes are connected by two logically contradictory types of links: positive and negative links. In a signed products network, two products can be complementary (purchased together) or substitutable (purchased instead of each other). Such contradictory types of links may play dramatically different roles in the spreading process of information, opinion, behaviour etc. In this work, we propose a self-avoiding pruning (SAP) random walk on a signed network to model e.g. a user's purchase activity on a signed products network. A SAP walk starts at a random node. At each step, the walker moves to a positive neighbour that is randomly selected, the previously visited node is removed and each of its negative neighbours are removed independently with a pruning probability r. We explored both analytically and numerically how signed network topological features influence the key performance of a SAP walk: the evolution of the pruned network resulted from the node removals, the length of a SAP walk and the visiting probability of each node. These findings in signed network models are further verified in two real-world signed networks. Our findings may inspire the design of recommender systems regarding how recommendations and competitions may influence consumers' purchases and products' popularity.

AB - A signed network represents how a set of nodes are connected by two logically contradictory types of links: positive and negative links. In a signed products network, two products can be complementary (purchased together) or substitutable (purchased instead of each other). Such contradictory types of links may play dramatically different roles in the spreading process of information, opinion, behaviour etc. In this work, we propose a self-avoiding pruning (SAP) random walk on a signed network to model e.g. a user's purchase activity on a signed products network. A SAP walk starts at a random node. At each step, the walker moves to a positive neighbour that is randomly selected, the previously visited node is removed and each of its negative neighbours are removed independently with a pruning probability r. We explored both analytically and numerically how signed network topological features influence the key performance of a SAP walk: the evolution of the pruned network resulted from the node removals, the length of a SAP walk and the visiting probability of each node. These findings in signed network models are further verified in two real-world signed networks. Our findings may inspire the design of recommender systems regarding how recommendations and competitions may influence consumers' purchases and products' popularity.

KW - random walk

KW - signed network

KW - self-avoiding walk

KW - OA-Fund TU Delft

U2 - 10.1088/1367-2630/ab060f

DO - 10.1088/1367-2630/ab060f

M3 - Article

VL - 21

JO - New Journal of Physics

T2 - New Journal of Physics

JF - New Journal of Physics

SN - 1367-2630

M1 - 035001

ER -

ID: 53392084