摘要
[研究目的]网络伪健康知识的广泛传播,对用户产生严重误导,给公众健康带来负面影响。探究基于证据质量的内容偏差,有助于从信息源发现其对用户误导效应的作用机制,从而为网络健康信息治理提供指导。[研究方法]探究了健康科普知识内容偏差及其效应的评估和测度方法,基于论证模型提炼出5种证据类型,并采用组态视角和模糊集定性比较分析探索了误导效应形成的主要路径。[研究结论]基于证据类型的组态分析结果显示,高误导效应的形成路径有5条,可识别为三种组态类型:低偏差论据误导型,面向具有系统性判断偏好和信息素养较高的用户;经验偏差误导型,面向偏好经验叙事的用户;专业偏差误导型,面向信息素养偏低、偏好启发式评估和权威依赖型用户。基于此,提出了针对各种组态类型的应对策略和实践措施。
[Research purpose]The widespread dissemination of online health misinformation has misleading effect on users and negative impact on public health.Exploring content bias based on evidence quality can help discover the mechanism of its misleading effect on users from information sources,thus provide guidance for health information governance.[Research method]This article explores the evaluation and measurement methods of bias in the content of online health knowledge and its effects.Based on argumentation models,five evidence types are extracted,and the pathways for the formation of misleading effects are explored using a configuration perspective and qualitative comparative analysis.[Research conclusion]The configuration analysis results based on evidence types show that there are 5 paths for the formation of high misleading effects,which can be identified as three types:Low argument bias,aiming at users with systematic judgment preferences and high information literacy;Experience bias,targeting users who prefer experiential narrative;Professional bias,targeting users with low information literacy,heuristic evaluation preference,and authority dependence.The article also proposes corresponding strategies and practical approaches for various configurational types.
作者
张薇薇
唐晓丹
黎洁
Zhang Weiwei;Tang Xiaodan;Li Jie(School of Management Science and Engineering,Nanjing University of Information Science&Technology,Nanjing 210044)
出处
《情报杂志》
CSSCI
北大核心
2024年第7期164-171,153,共9页
Journal of Intelligence
基金
国家社会科学基金一般项目“网络伪健康知识的生成机理、效应及评估机制研究”(编号:22BTQ056)
江苏省高校哲学社会科学研究重大项目(编号:2022SJZD096)研究成果。
关键词
网络伪健康知识
证据类型
内容偏差
偏差效应
误导效应
组态分析
模糊集定性比较分析
pseudo health knowledge online
evidence types
content bias
bias effect
misleading effect
configurational analysis
fuzzy-set qualitative comparative analysis(fsQCA)
作者简介
张薇薇,女,1978年生,博士,教授,研究方向:网络信息资源管理、用户信息行为;唐晓丹,男,1998年生,硕士研究生,研究方向:网络健康信息分析;黎洁,女,2000年生,硕士研究生,研究方向:用户健康信息行为。
