Xinyue Hao , Dapeng Dong , Chang Liu , Emrah Demir , Samuel Fosso Wamba
{"title":"食品安全意见传播的易感感染扩散:基础设施驱动的传播和行为嵌入的实质","authors":"Xinyue Hao , Dapeng Dong , Chang Liu , Emrah Demir , Samuel Fosso Wamba","doi":"10.1016/j.eswa.2025.128886","DOIUrl":null,"url":null,"abstract":"<div><div>This study examines how food safety information disseminates across three structurally distinct Chinese social media platforms, Weibo, TikTok, and Xiaohongshu (XHS), during crisis events. Rather than serving as neutral transmission channels, these platforms are conceptualized as dynamic Information Service Systems (ISS), in which algorithmic infrastructures and content substances co-produce public meaning, emotional salience, and trust dynamics. Drawing on the Substance–Infrastructure (S-I) model, specifically Type II logic, where infrastructure drives substance, we theorize that technical mechanisms such as feed algorithms, trending systems, and visibility logics interact with semantic features like emotional tone, media modality, and narrative framing to shape the velocity, reach, and epistemic reliability of crisis communication. Employing a mixed-methods design that combines temporal Exponential Random Graph Models (ERGM), Susceptible-Infected (SI) diffusion simulations, and BERT-based sentiment analysis, we identify how different network structures, decentralized, centralized, and hybrid, interact with conformity, homophily, and neophilia to produce platform-specific information ecologies. TikTok’s architecture enables high-speed virality with minimal deliberative anchoring, limiting the platform’s ability to support trust repair; XHS facilitates high-affinity trust ecosystems led by key opinion leaders, but is vulnerable to echo chambers and insular misinformation; Weibo, with its hybrid infrastructure, supports rapid escalation and multi-directional discourse, but suffers from volatility in trust due to inconsistent epistemic control. These distinct affordances explain the asymmetric amplification of food safety narratives and the divergent trajectories of public trust, consolidation, polarization, or collapse, across platforms. As a contribution, the study introduces the Integrated Design and Operation Management (IDOM) framework, which positions platforms as reflexive control systems that must adapt to real-time signals of uncertainty and trust decay. It further underscores the need for resilient public governance that aligns institutional interventions with platform-specific logics and user cognitive baselines, advocating for a coordinated socio-technical ecosystem capable of sustaining trustworthy, inclusive, and responsive food safety communication in the digital era.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"295 ","pages":"Article 128886"},"PeriodicalIF":7.5000,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Susceptible-infected diffusion of food safety opinion dissemination: Infrastructure-driven spread and behavior-embedded substance\",\"authors\":\"Xinyue Hao , Dapeng Dong , Chang Liu , Emrah Demir , Samuel Fosso Wamba\",\"doi\":\"10.1016/j.eswa.2025.128886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study examines how food safety information disseminates across three structurally distinct Chinese social media platforms, Weibo, TikTok, and Xiaohongshu (XHS), during crisis events. Rather than serving as neutral transmission channels, these platforms are conceptualized as dynamic Information Service Systems (ISS), in which algorithmic infrastructures and content substances co-produce public meaning, emotional salience, and trust dynamics. Drawing on the Substance–Infrastructure (S-I) model, specifically Type II logic, where infrastructure drives substance, we theorize that technical mechanisms such as feed algorithms, trending systems, and visibility logics interact with semantic features like emotional tone, media modality, and narrative framing to shape the velocity, reach, and epistemic reliability of crisis communication. Employing a mixed-methods design that combines temporal Exponential Random Graph Models (ERGM), Susceptible-Infected (SI) diffusion simulations, and BERT-based sentiment analysis, we identify how different network structures, decentralized, centralized, and hybrid, interact with conformity, homophily, and neophilia to produce platform-specific information ecologies. TikTok’s architecture enables high-speed virality with minimal deliberative anchoring, limiting the platform’s ability to support trust repair; XHS facilitates high-affinity trust ecosystems led by key opinion leaders, but is vulnerable to echo chambers and insular misinformation; Weibo, with its hybrid infrastructure, supports rapid escalation and multi-directional discourse, but suffers from volatility in trust due to inconsistent epistemic control. These distinct affordances explain the asymmetric amplification of food safety narratives and the divergent trajectories of public trust, consolidation, polarization, or collapse, across platforms. As a contribution, the study introduces the Integrated Design and Operation Management (IDOM) framework, which positions platforms as reflexive control systems that must adapt to real-time signals of uncertainty and trust decay. It further underscores the need for resilient public governance that aligns institutional interventions with platform-specific logics and user cognitive baselines, advocating for a coordinated socio-technical ecosystem capable of sustaining trustworthy, inclusive, and responsive food safety communication in the digital era.</div></div>\",\"PeriodicalId\":50461,\"journal\":{\"name\":\"Expert Systems with Applications\",\"volume\":\"295 \",\"pages\":\"Article 128886\"},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2025-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert Systems with Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0957417425025035\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957417425025035","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Susceptible-infected diffusion of food safety opinion dissemination: Infrastructure-driven spread and behavior-embedded substance
This study examines how food safety information disseminates across three structurally distinct Chinese social media platforms, Weibo, TikTok, and Xiaohongshu (XHS), during crisis events. Rather than serving as neutral transmission channels, these platforms are conceptualized as dynamic Information Service Systems (ISS), in which algorithmic infrastructures and content substances co-produce public meaning, emotional salience, and trust dynamics. Drawing on the Substance–Infrastructure (S-I) model, specifically Type II logic, where infrastructure drives substance, we theorize that technical mechanisms such as feed algorithms, trending systems, and visibility logics interact with semantic features like emotional tone, media modality, and narrative framing to shape the velocity, reach, and epistemic reliability of crisis communication. Employing a mixed-methods design that combines temporal Exponential Random Graph Models (ERGM), Susceptible-Infected (SI) diffusion simulations, and BERT-based sentiment analysis, we identify how different network structures, decentralized, centralized, and hybrid, interact with conformity, homophily, and neophilia to produce platform-specific information ecologies. TikTok’s architecture enables high-speed virality with minimal deliberative anchoring, limiting the platform’s ability to support trust repair; XHS facilitates high-affinity trust ecosystems led by key opinion leaders, but is vulnerable to echo chambers and insular misinformation; Weibo, with its hybrid infrastructure, supports rapid escalation and multi-directional discourse, but suffers from volatility in trust due to inconsistent epistemic control. These distinct affordances explain the asymmetric amplification of food safety narratives and the divergent trajectories of public trust, consolidation, polarization, or collapse, across platforms. As a contribution, the study introduces the Integrated Design and Operation Management (IDOM) framework, which positions platforms as reflexive control systems that must adapt to real-time signals of uncertainty and trust decay. It further underscores the need for resilient public governance that aligns institutional interventions with platform-specific logics and user cognitive baselines, advocating for a coordinated socio-technical ecosystem capable of sustaining trustworthy, inclusive, and responsive food safety communication in the digital era.
期刊介绍:
Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.