Cascade of edge activation in networks

Gabriel Lopez Zenarosa; Alexander Veremyev; Eduardo L. Pasiliao

doi:10.1007/978-3-030-34980-6_16

Cascade of edge activation in networks

Gabriel Lopez Zenarosa
, Alexander Veremyev
, Eduardo L. Pasiliao

Dean's Office, College of Business

University of Central Florida
Air Force Research Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We consider models for inducing a maximum cascade of activating connections in social networks over a finite horizon subject to budget constraints. These models reflect problems of choosing an initial set of pairs of individuals to connect or engage in order to maximize the cascade of new connections or engagements over time. We assume connections activate as a result of past activation of neighboring connections. We show that the optimization problem is NP-hard, and we provide a method for improving computations.

Original language	English
Title of host publication	Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings
Editors	Andrea Tagarelli, Hanghang Tong
Publisher	Springer
Pages	141-147
Number of pages	7
ISBN (Print)	9783030349790
DOIs	https://doi.org/10.1007/978-3-030-34980-6_16
State	Published - 2019
Event	8th International Conference on Computational Data and Social Networks, CSoNet 2019 - Ho Chi Minh City, Viet Nam Duration: Nov 18 2019 → Nov 20 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11917 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Computational Data and Social Networks, CSoNet 2019
Country/Territory	Viet Nam
City	Ho Chi Minh City
Period	11/18/19 → 11/20/19

Keywords

Cascade
Diffusion
Edge activation
Social networks

Access to Document

10.1007/978-3-030-34980-6_16

Cite this

Zenarosa, G. L., Veremyev, A., & Pasiliao, E. L. (2019). Cascade of edge activation in networks. In A. Tagarelli, & H. Tong (Eds.), Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings (pp. 141-147). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11917 LNCS). Springer. https://doi.org/10.1007/978-3-030-34980-6_16

Zenarosa, Gabriel Lopez ; Veremyev, Alexander ; Pasiliao, Eduardo L. / Cascade of edge activation in networks. Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings. editor / Andrea Tagarelli ; Hanghang Tong. Springer, 2019. pp. 141-147 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{499a7b176d024a68bba6831972f433b9,

title = "Cascade of edge activation in networks",

abstract = "We consider models for inducing a maximum cascade of activating connections in social networks over a finite horizon subject to budget constraints. These models reflect problems of choosing an initial set of pairs of individuals to connect or engage in order to maximize the cascade of new connections or engagements over time. We assume connections activate as a result of past activation of neighboring connections. We show that the optimization problem is NP-hard, and we provide a method for improving computations.",

keywords = "Cascade, Diffusion, Edge activation, Social networks",

author = "Zenarosa, \{Gabriel Lopez\} and Alexander Veremyev and Pasiliao, \{Eduardo L.\}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 8th International Conference on Computational Data and Social Networks, CSoNet 2019 ; Conference date: 18-11-2019 Through 20-11-2019",

year = "2019",

doi = "10.1007/978-3-030-34980-6\_16",

language = "English",

isbn = "9783030349790",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "141--147",

editor = "Andrea Tagarelli and Hanghang Tong",

booktitle = "Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings",

}

Zenarosa, GL, Veremyev, A & Pasiliao, EL 2019, Cascade of edge activation in networks. in A Tagarelli & H Tong (eds), Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11917 LNCS, Springer, pp. 141-147, 8th International Conference on Computational Data and Social Networks, CSoNet 2019, Ho Chi Minh City, Viet Nam, 11/18/19. https://doi.org/10.1007/978-3-030-34980-6_16

Cascade of edge activation in networks. / Zenarosa, Gabriel Lopez; Veremyev, Alexander; Pasiliao, Eduardo L.
Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings. ed. / Andrea Tagarelli; Hanghang Tong. Springer, 2019. p. 141-147 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11917 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Cascade of edge activation in networks

AU - Zenarosa, Gabriel Lopez

AU - Veremyev, Alexander

AU - Pasiliao, Eduardo L.

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - We consider models for inducing a maximum cascade of activating connections in social networks over a finite horizon subject to budget constraints. These models reflect problems of choosing an initial set of pairs of individuals to connect or engage in order to maximize the cascade of new connections or engagements over time. We assume connections activate as a result of past activation of neighboring connections. We show that the optimization problem is NP-hard, and we provide a method for improving computations.

AB - We consider models for inducing a maximum cascade of activating connections in social networks over a finite horizon subject to budget constraints. These models reflect problems of choosing an initial set of pairs of individuals to connect or engage in order to maximize the cascade of new connections or engagements over time. We assume connections activate as a result of past activation of neighboring connections. We show that the optimization problem is NP-hard, and we provide a method for improving computations.

KW - Cascade

KW - Diffusion

KW - Edge activation

KW - Social networks

UR - https://www.scopus.com/pages/publications/85077779466

U2 - 10.1007/978-3-030-34980-6_16

DO - 10.1007/978-3-030-34980-6_16

M3 - Conference contribution

AN - SCOPUS:85077779466

SN - 9783030349790

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 141

EP - 147

BT - Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings

A2 - Tagarelli, Andrea

A2 - Tong, Hanghang

PB - Springer

T2 - 8th International Conference on Computational Data and Social Networks, CSoNet 2019

Y2 - 18 November 2019 through 20 November 2019

ER -

Zenarosa GL, Veremyev A, Pasiliao EL. Cascade of edge activation in networks. In Tagarelli A, Tong H, editors, Computational Data and Social Networks - 8th International Conference, CSoNet 2019, Proceedings. Springer. 2019. p. 141-147. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-34980-6_16

Cascade of edge activation in networks

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Keywords

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