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Modeling and analyzing cross-transmission dynamics of related information co-propagation

The dissemination of one public hot event is usually affected by some related information, and the implication of co-propagation by different information is critical for the integrated analysis. To help in designing effective communication strategies during the whole event, we propose the cross-tran...

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Autores principales: Yin, Fulian, Shao, Xueying, Tang, Biao, Xia, Xinyu, Wu, Jianhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801523/
https://www.ncbi.nlm.nih.gov/pubmed/33432014
http://dx.doi.org/10.1038/s41598-020-79503-8
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author Yin, Fulian
Shao, Xueying
Tang, Biao
Xia, Xinyu
Wu, Jianhong
author_facet Yin, Fulian
Shao, Xueying
Tang, Biao
Xia, Xinyu
Wu, Jianhong
author_sort Yin, Fulian
collection PubMed
description The dissemination of one public hot event is usually affected by some related information, and the implication of co-propagation by different information is critical for the integrated analysis. To help in designing effective communication strategies during the whole event, we propose the cross-transmission susceptible-forwarding-immune (CT-SFI) model to describe the dynamics of co-propagation particularly with focus on the cross-transmission effects. This model is based on the forwarding quantity and takes into account the behavior that users may have a strong attraction or continuous attraction within or without an active time after contacting one information. Data fitting using the real data of Chinese Sina-microblog can accurately parameterize the model and parameter sensitivity analysis gives some strategies for co-propagation.
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spelling pubmed-78015232021-01-12 Modeling and analyzing cross-transmission dynamics of related information co-propagation Yin, Fulian Shao, Xueying Tang, Biao Xia, Xinyu Wu, Jianhong Sci Rep Article The dissemination of one public hot event is usually affected by some related information, and the implication of co-propagation by different information is critical for the integrated analysis. To help in designing effective communication strategies during the whole event, we propose the cross-transmission susceptible-forwarding-immune (CT-SFI) model to describe the dynamics of co-propagation particularly with focus on the cross-transmission effects. This model is based on the forwarding quantity and takes into account the behavior that users may have a strong attraction or continuous attraction within or without an active time after contacting one information. Data fitting using the real data of Chinese Sina-microblog can accurately parameterize the model and parameter sensitivity analysis gives some strategies for co-propagation. Nature Publishing Group UK 2021-01-11 /pmc/articles/PMC7801523/ /pubmed/33432014 http://dx.doi.org/10.1038/s41598-020-79503-8 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yin, Fulian
Shao, Xueying
Tang, Biao
Xia, Xinyu
Wu, Jianhong
Modeling and analyzing cross-transmission dynamics of related information co-propagation
title Modeling and analyzing cross-transmission dynamics of related information co-propagation
title_full Modeling and analyzing cross-transmission dynamics of related information co-propagation
title_fullStr Modeling and analyzing cross-transmission dynamics of related information co-propagation
title_full_unstemmed Modeling and analyzing cross-transmission dynamics of related information co-propagation
title_short Modeling and analyzing cross-transmission dynamics of related information co-propagation
title_sort modeling and analyzing cross-transmission dynamics of related information co-propagation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801523/
https://www.ncbi.nlm.nih.gov/pubmed/33432014
http://dx.doi.org/10.1038/s41598-020-79503-8
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