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Information diffusion in signed networks
Information diffusion has been widely discussed in various disciplines including sociology, economics, physics or computer science. In this paper, we generalize the linear threshold model in signed networks consisting of both positive and negative links. We analyze the dynamics of the spread of info...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6818773/ https://www.ncbi.nlm.nih.gov/pubmed/31661504 http://dx.doi.org/10.1371/journal.pone.0224177 |
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author | He, Xiaochen Du, Haifeng Feldman, Marcus W. Li, Guangyu |
author_facet | He, Xiaochen Du, Haifeng Feldman, Marcus W. Li, Guangyu |
author_sort | He, Xiaochen |
collection | PubMed |
description | Information diffusion has been widely discussed in various disciplines including sociology, economics, physics or computer science. In this paper, we generalize the linear threshold model in signed networks consisting of both positive and negative links. We analyze the dynamics of the spread of information based on balance theory, and find that a signed network can generate path dependence while structural balance can help remove the path dependence when seeded with balanced initialized active nodes. Simulation shows that the diffusion of information based on positive links contradicts that based on negative links. More positive links in signed networks are more likely to activate nodes and remove path dependence, but they can reduce predictability that is based on active states. We also find that a balanced structure can facilitate both the magnitude and speed of information diffusion, remove the path dependence, and cause polarization. |
format | Online Article Text |
id | pubmed-6818773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-68187732019-11-01 Information diffusion in signed networks He, Xiaochen Du, Haifeng Feldman, Marcus W. Li, Guangyu PLoS One Research Article Information diffusion has been widely discussed in various disciplines including sociology, economics, physics or computer science. In this paper, we generalize the linear threshold model in signed networks consisting of both positive and negative links. We analyze the dynamics of the spread of information based on balance theory, and find that a signed network can generate path dependence while structural balance can help remove the path dependence when seeded with balanced initialized active nodes. Simulation shows that the diffusion of information based on positive links contradicts that based on negative links. More positive links in signed networks are more likely to activate nodes and remove path dependence, but they can reduce predictability that is based on active states. We also find that a balanced structure can facilitate both the magnitude and speed of information diffusion, remove the path dependence, and cause polarization. Public Library of Science 2019-10-29 /pmc/articles/PMC6818773/ /pubmed/31661504 http://dx.doi.org/10.1371/journal.pone.0224177 Text en © 2019 He et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article He, Xiaochen Du, Haifeng Feldman, Marcus W. Li, Guangyu Information diffusion in signed networks |
title | Information diffusion in signed networks |
title_full | Information diffusion in signed networks |
title_fullStr | Information diffusion in signed networks |
title_full_unstemmed | Information diffusion in signed networks |
title_short | Information diffusion in signed networks |
title_sort | information diffusion in signed networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6818773/ https://www.ncbi.nlm.nih.gov/pubmed/31661504 http://dx.doi.org/10.1371/journal.pone.0224177 |
work_keys_str_mv | AT hexiaochen informationdiffusioninsignednetworks AT duhaifeng informationdiffusioninsignednetworks AT feldmanmarcusw informationdiffusioninsignednetworks AT liguangyu informationdiffusioninsignednetworks |