{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T10:51:00Z","timestamp":1776682260028,"version":"3.51.2"},"reference-count":55,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T00:00:00Z","timestamp":1686528000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Scientific Research Foundation of Shantou University","award":["NTF20026"],"award-info":[{"award-number":["NTF20026"]}]},{"name":"Scientific Research Foundation of Shantou University","award":["NTF21041"],"award-info":[{"award-number":["NTF21041"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>As a pandemic emerges, information on epidemic prevention disseminates among the populace, and the propagation of that information interacts with the proliferation of the disease. Mass media serve a pivotal function in facilitating the dissemination of epidemic-related information. Investigating coupled information\u2013epidemic dynamics, while accounting for the promotional effect of mass media in information dissemination, is of significant practical relevance. Nonetheless, in the extant research, scholars predominantly employ an assumption that mass media broadcast to all individuals equally within the network: this assumption overlooks the practical constraint imposed by the substantial social resources required to accomplish such comprehensive promotion. In response, this study introduces a coupled information\u2013epidemic spreading model with mass media that can selectively target and disseminate information to a specific proportion of high-degree nodes. We employed a microscopic Markov chain methodology to scrutinize our model, and we examined the influence of the various model parameters on the dynamic process. The findings of this study reveal that mass media broadcasts directed towards high-degree nodes within the information spreading layer can substantially reduce the infection density of the epidemic, and raise the spreading threshold of the epidemic. Additionally, as the mass media broadcast proportion increases, the suppression effect on the disease becomes stronger. Moreover, with a constant broadcast proportion, the suppression effect of mass media promotion on epidemic spreading within the model is more pronounced in a multiplex network with a negative interlayer degree correlation, compared to scenarios with positive or absent interlayer degree correlation.<\/jats:p>","DOI":"10.3390\/e25060927","type":"journal-article","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T02:56:34Z","timestamp":1686624994000},"page":"927","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Coupled Information\u2013Epidemic Spreading Dynamics with Selective Mass Media"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0542-3913","authenticated-orcid":false,"given":"Jiajun","family":"Xian","sequence":"first","affiliation":[{"name":"Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zongyi","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e19659","DOI":"10.2196\/19659","article-title":"Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation","volume":"22","author":"Tangcharoensathien","year":"2020","journal-title":"J. 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