移动社交媒体健康信息规避行为用户画像实证研究

An Empirical Study on User Portrait of Health Information Evasion Behavior in Mobile Social Media

[目的/意义]探究新媒体环境下,不同移动社交媒体用户健康信息规避的影响因素与表现差异,抽取标签要素并结合FBM理论模型进行用户画像分析,为健康服务机构深度了解用户群体特征、精准把握用户类型提供理论与实践指导。[方法/过程]基于半结构访谈收集样本资料,通过扎根理论抽取要素标签,以在校学生、公司职员与农民为调查对象,通过K-means聚类算法对移动社交媒体健康信息规避用户进行聚类分析。[结果/结论]研究得出,移动社交媒体健康信息规避用户可分为利用规避型、吸收规避型、暴露规避型与屏蔽规避型4种用户画像群体结构,且不同用户群体显著触发因素与规避表现有所差异。

[Purpose/Significance]Explore the influencing factors and performance differences of different mobile social media users health information avoidance under the new media environment,extract the tag elements and conduct user portrait analysis in combination with the FBM theoretical model,so as to provide theoretical and practical guidance for health service institutions to deeply understand the characteristics of user groups and accurately grasp the types of users.[Method/Process]Collect sample data based on semi-structured interviews,extract factor labels through grounded theory,take students,company employees and farmers as the survey objects,and use K-means clustering algorithm to cluster mobile social media health information to avoid users.[Result/Conclusion] The research shows that mobile social media health information evading users can be divided into four user portrait group structures,namely,using evasive,absorbing evasive,exposing evasive and shielding evasive,and the significant trigger factors and evasive performance of different user groups are different.