Efficient and effective influence maximization in large-scale social networks via two frameworks-Reference-Cited by-同舟云学术

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Efficient and effective influence maximization in large-scale social networks via two frameworks

Published:2019-07 Issue: Volume:526 Page:120966
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Yuan Jinliang,Zhang Ruisheng,Tang Jianxin,Hu Rongjing,Wang Zepeng,Li Huan

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities, China

CERNET Innovation Project

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistics and Probability

Reference55 articles.

1. Spontaneous emergence of social influence in online systems;Onnela;Proc. Natl. Acad. Sci. USA,2010

2. A 61-million-person experiment in social influence and political mobilization;Bond;Nature,2012

3. Integrating social networks and human social motives to achieve social influence at scale;Contractor;Proc. Natl. Acad. Sci.,2014

4. Scalable influence maximization for prevalent viral marketing in large-scale social networks;Chen,2010

5. Friend recommendation with content spread enhancement in social networks;Yu;Inform. Sci.,2015

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2. Maximizing the spread of conservation initiatives in social networks;Conservation Science and Practice;2022-06-21

3. Modeling Rumor Diffusion Process With the Consideration of Individual Heterogeneity: Take the Imported Food Safety Issue as an Example During the COVID-19 Pandemic;Frontiers in Public Health;2022-03-07

4. A probability-driven structure-aware algorithm for influence maximization under independent cascade model;Physica A: Statistical Mechanics and its Applications;2021-12

5. CS- and GA-based hybrid evolutionary sampling algorithm for large-scale social networks;Social Network Analysis and Mining;2021-11-09

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