图书情报工作

图书情报工作 >

2021 , Vol. 65 >Issue 8: 65 - 73

DOI: https://doi.org/10.13266/j.issn.0252-3116.2021.08.007

情报研究

突发公共卫生事件社交媒体用户健康信息焦虑影响因素识别研究

  • 张艳丰 ,
  • 刘亚丽 ,
  • 邹凯
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  • 湘潭大学公共管理学院 湘潭 411105
张艳丰(ORCID:0000-0001-9374-2449),讲师,博士,硕士生导师,E-mail:zyfzzia@163.com;刘亚丽(ORCID:0000-0002-2405-4084),硕士研究生;邹凯(ORCID:0000-0002-3591-9821),教授,博士,博士生导师。

收稿日期: 2020-11-10

  修回日期: 2021-01-16

  网络出版日期: 2021-06-02

基金资助

本文系国家社会科学基金一般项目"大数据环境下智慧城市信息安全困境及应对策略研究"（项目编号：18BTQ055）研究成果之一。

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Identification of Influencing Factors of Social Media Users' Health Information Anxiety in Public Health Emergencies

  • Zhang Yanfeng ,
  • Liu Yali ,
  • Zou Kai
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  • School of Public Management, Xiangtan University, Xiangtan 411105

Received date: 2020-11-10

  Revised date: 2021-01-16

  Online published: 2021-06-02

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摘要

[目的/意义] 分析突发公共卫生事件背景下社交媒体用户健康信息焦虑的影响因素，为国内外学者进一步探究社交媒体用户健康信息焦虑问题提供理论与应用参考。[方法/过程] 基于信息生态理论，从信息人、信息、信息环境和信息技术4个维度提取要素，结合改进的解释结构模型（ISM）和交叉矩阵相乘法（MICMAC）对社交媒体用户健康信息焦虑的影响因素进行关联路径分析和层级模型构建。[结果/结论] 研究结果表明解释结构模型中的直接层因素、中间层因素和根源层因素与交叉矩阵相乘法中所得出的独立群因素、自治群因素和依赖群因素在影响性质上具有高度的一致性，进一步证明解释结构模型对影响因素的关联分析和层级分类具有可行性。

关键词： 突发公共卫生事件; 社交媒体用户; 健康信息焦虑; 影响因素

本文引用格式

张艳丰 , 刘亚丽 , 邹凯 . 突发公共卫生事件社交媒体用户健康信息焦虑影响因素识别研究[J]. 图书情报工作, 2021 , 65(8) : 65 -73 . DOI: 10.13266/j.issn.0252-3116.2021.08.007

Abstract

[Purpose/significance] Analyzing the influencing factors of social media users' health information anxiety in the context of public health emergencies can provide theoretical and applied reference for domestic and foreign scholars to further explore the health information anxiety of social media users.[Method/process] Based on information ecology theory, factors are extracted from four dimensions of information person, information, information environment and information technology. The correlation path analysis and hierarchical model construction were carried out for the influencing factors of health information anxiety of social media users combined with the improved ISM model and the cross matrix multiplication (MICMAC).[Result/conclusion] The results show that the direct layer factors, intermediate layer factors and root layer factors in the explanatory structural model have a high degree of agreement with the independent group factors, autonomous group factors and dependent group factors in the cross matrix multiplication, and further proves that the explanatory structure model is feasible for correlation analysis and hierarchical classification of influencing factors.

Key words： public health emergency; social media users; health information anxiety; influencing factors

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