基于用户信息行为的微信健康信息关注度研究

Research on Collective Attention to Health Information on WeChat through Analyzing Information Behaviors of Users

【目的/意义】旨在自动分析用户对微信健康信息的关注度。【方法/过程】构建了微信健康信息关注度分析模型,以丁香医生、丁香家庭健康和脉脉养生公众号推送的健康信息作为数据来源,识别微信健康信息的类别和主题分布,基于对用户信息行为的分析来评估用户对健康信息的关注度。【结果/结论】微信公众平台推送的健康信息主要有12类;通过分析用户对微信健康信息关注度发现,健康风险、饮食、药物、身体活动和癌症主题受关注程度较高;用户对各主题健康信息的关注程度与微信公众平台的信息供应分布并不一致。本研究提出的用户关注度自动分析模型具备可以移植性,是对传统关注度研究方法的有效补充。

【Purpose/significance】This paper aims to analyze users’attention to WeChat health information automatically.【Method/process】In this paper,the automated analysis model of collective attention to health information on WeChat was developed.We collected the health information pushed by the public accounts of'dingxiangyisheng','baojiandaifu'and'mmaijiu'as experimental data.The topic distribution of WeChat health information was mined and identified,and the collective attention to health information was evaluated through the analysis of users’information behaviors.【Result/conclusion】WeChat public platform mainly pushes 12 types of health information.By analyzing users’attention to WeChat health information,it is found that health risks,diet,drugs,physical activities,cancer are highly concerned.Users’attention to health information on each subject is not consistent with the release distribution of WeChat public platform.The automated analysis model of collective attention proposed in this study is portable and it is an effective supplement to the traditional research methods of user concern.