图书情报工作2024,Vol.68Issue(16) :117-128.DOI:10.13266/j.issn.0252-3116.2024.16.010

移动社交媒体老年用户虚假信息应对行为画像实证研究

An Empirical Study on Disinformation Coping Behavior Portraits of Elderly Mobile Social Media Users

毛太田 刘捷 毛俊博
图书情报工作2024,Vol.68Issue(16) :117-128.DOI:10.13266/j.issn.0252-3116.2024.16.010

移动社交媒体老年用户虚假信息应对行为画像实证研究

An Empirical Study on Disinformation Coping Behavior Portraits of Elderly Mobile Social Media Users

毛太田 1刘捷 1毛俊博1
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作者信息

  • 1. 湘潭大学公共管理学院 湘潭 411105
  • 折叠

摘要

[目的/意义]探究社交媒体平台老年用户应对虚假信息的情感和行为表征差异,为相关平台或服务机构深入了解用户特征、准确把握用户类型、精准开展帮扶工作提供科学指导.[方法/过程]通过访谈收集文本资料,借助扎根理论抽取要素标签并结合应对理论构建用户画像概念模型,采用K-means聚类方法进行实证分析得出4类具有显著差异特征的用户群体画像类型.[结果/结论]根据各项标签特征将移动社交媒体老年用户虚假信息应对行为画像类型分为冷静求证型、担忧关注型、行为替代型和忽略回避型4类,不同类型用户群体在压力感知和应对表现方面都存在显著性差异.

Abstract

[Purpose/Significance]This study explores the differences in emotional and behavioral response of elderly users to disinformation on social media platforms.It aims to provide scientific guidance for relevant plat-forms or service organizations to deeply understand user characteristics,accurately identify user types,and accu-rately carry out help work.[Method/Process]Text data were collected through interviews,and element labels were extracted using grounded theory.A conceptual model of user portrait was then constructed with the combination of coping theory.Four types of user group portrait types with significant differences were obtained through empirical analysis by K-means clustering method.[Result/Conclusion]According to various label characteristics,four cate-gories of disinformation coping behavior portraits are identified for elderly mobile social media users:cool-seeking type,worried and concerned type,behavioral substitution type and ignoring and avoiding type.These distinct user groups have significant differences in pressure perception,strategy choice and coping performance.

关键词

老年用户/虚假信息应对/用户画像/K-means

Key words

elderly users/disinformation response/user portrait/K-means

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出版年

2024
图书情报工作
中国科学院文献情报中心

图书情报工作

CSTPCDCSSCICHSSCD北大核心
影响因子:2.203
ISSN:0252-3116
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