Positive influence dominating sets in power-law graphs

Wei Zhang; Weili Wu; Feng Wang; Kuai Xu

doi:10.1007/s13278-011-0033-9

Positive influence dominating sets in power-law graphs

Wei Zhang, Weili Wu, Feng Wang, Kuai Xu

Mathematical and Natural Sciences, School of (SMNS)

Research output: Contribution to journal › Article › peer-review

26 Scopus citations

Abstract

Finding the minimum Positive Influence Dominating Set (PIDS) is a problem arisen from the social network applications. The problem has been studied on general random graphs. However, the social networks is presented more precisely by power-law graphs. One of the most important properties of social networks is the power-law degree distribution. In this paper, we focus on the PIDS problem in power-law graphs and prove that the greedy algorithm has a constant approximation ratio. Simulation results also demonstrate that greedy algorithm can effectively select a small scale PIDS set.

Original language	English (US)
Pages (from-to)	31-37
Number of pages	7
Journal	Social Network Analysis and Mining
Volume	2
Issue number	1
DOIs	https://doi.org/10.1007/s13278-011-0033-9
State	Published - Jan 1 2012

Keywords

Greedy algorithm
Positive influence dominating set problem
Power-law distribution
Social networks

ASJC Scopus subject areas

Information Systems
Communication
Media Technology
Human-Computer Interaction
Computer Science Applications

Access to Document

10.1007/s13278-011-0033-9

Cite this

@article{35c2c22c189d4f8984b5657a1d692a14,

title = "Positive influence dominating sets in power-law graphs",

abstract = "Finding the minimum Positive Influence Dominating Set (PIDS) is a problem arisen from the social network applications. The problem has been studied on general random graphs. However, the social networks is presented more precisely by power-law graphs. One of the most important properties of social networks is the power-law degree distribution. In this paper, we focus on the PIDS problem in power-law graphs and prove that the greedy algorithm has a constant approximation ratio. Simulation results also demonstrate that greedy algorithm can effectively select a small scale PIDS set.",

keywords = "Greedy algorithm, Positive influence dominating set problem, Power-law distribution, Social networks",

author = "Wei Zhang and Weili Wu and Feng Wang and Kuai Xu",

note = "Funding Information: This work is supported in part by National Science Foundation under grants CNS1016320 and CCF0829993. Publisher Copyright: {\textcopyright} 2011, Springer-Verlag.",

year = "2012",

month = jan,

day = "1",

doi = "10.1007/s13278-011-0033-9",

language = "English (US)",

volume = "2",

pages = "31--37",

journal = "Social Network Analysis and Mining",

issn = "1869-5450",

publisher = "Springer Wien",

number = "1",

}

TY - JOUR

T1 - Positive influence dominating sets in power-law graphs

AU - Zhang, Wei

AU - Wu, Weili

AU - Wang, Feng

AU - Xu, Kuai

PY - 2012/1/1

Y1 - 2012/1/1

N2 - Finding the minimum Positive Influence Dominating Set (PIDS) is a problem arisen from the social network applications. The problem has been studied on general random graphs. However, the social networks is presented more precisely by power-law graphs. One of the most important properties of social networks is the power-law degree distribution. In this paper, we focus on the PIDS problem in power-law graphs and prove that the greedy algorithm has a constant approximation ratio. Simulation results also demonstrate that greedy algorithm can effectively select a small scale PIDS set.

AB - Finding the minimum Positive Influence Dominating Set (PIDS) is a problem arisen from the social network applications. The problem has been studied on general random graphs. However, the social networks is presented more precisely by power-law graphs. One of the most important properties of social networks is the power-law degree distribution. In this paper, we focus on the PIDS problem in power-law graphs and prove that the greedy algorithm has a constant approximation ratio. Simulation results also demonstrate that greedy algorithm can effectively select a small scale PIDS set.

KW - Greedy algorithm

KW - Positive influence dominating set problem

KW - Power-law distribution

KW - Social networks

UR - http://www.scopus.com/inward/record.url?scp=84874280441&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84874280441&partnerID=8YFLogxK

U2 - 10.1007/s13278-011-0033-9

DO - 10.1007/s13278-011-0033-9

M3 - Article

AN - SCOPUS:84874280441

SN - 1869-5450

VL - 2

SP - 31

EP - 37

JO - Social Network Analysis and Mining

JF - Social Network Analysis and Mining

IS - 1

ER -

Positive influence dominating sets in power-law graphs

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this