摘要
目的:优化在线健康社区用户画像模型,全面客观地揭示用户的多维度特征,基于用户画像提出社区用户个性化及社群化服务的建议,提升在线健康社区社会支持服务功能及用户体验。方法:利用模糊逻辑从用户基本属性、社交、兴趣、情感倾向4个维度优化在线健康社区用户画像模型,并对在线健康社区用户进行分类,在“知乎”平台糖尿病话题中选取不同类型用户中的典型用户进行应用研究。结果:根据用户黏性高低、内容贡献量高低、正负情感倾向将3934名知乎糖尿病话题用户划分为低黏性低产积极、低黏性低产消极、低黏性高产积极等8类用户,每类选取2位典型用户用以刻画用户形象;社区运营者可从定期推送社区信息、设计或完善发帖奖励机制、提供情感咨询服务等方面管理社区用户。结论:经过优化的在线健康社区用户画像可准确客观地揭示用户社交行为、兴趣需求、情感倾向等特征,有助于社区运营者提供精准的信息服务和丰富各类社会支持服务,促进社区长久发展。
Objective To optimize the user portrait model of online health community, to reveal the multidimensional characteristics of users comprehensively and objectively, to suggest personalized and community-based services for users based on user portrait, and to enhance the functions and user experience of community social support services. Methods Fuzzy logic was used to optimize the user portrait model of online health community in four dimensions: users’ basic attributes, social interactions, interests, and emotional tendencies;the online health community users were then classified, and typical Zhihu users of diabetes topics were selected from different types of users for application research. Results According to the levels of user viscosity, content contribution, and emotional tendency, the 3,934 Zhihu users of diabetes topics were classified into 8 categories: low-viscosity and low-productivity positive users, low-viscosity and low-productivity negative users, and low-viscosity and high-productivity positive users, etc. Two typical users from each category were selected to portray the user images, and the community operators could manage the community users by pushing community information regularly, designing or improving the posting reward mechanism, and providing emotional counseling services, etc. Conclusion The optimized user portrait model of online health community can accurately and objectively reveal the characteristics of users’ social behaviors, interests and needs, and emotional tendencies, which is helpful for community operators to provide accurate information services, enrich various social support services, and promote the long-term development of the community.
作者
王巍洁
任慧玲
李晓瑛
张云秋
张慧芳
冯凤翔
WANG Wei-jie;REN Hui-ling;LI Xiao-ying;ZHANG Yun-qiu;ZHANG Hui-fang;FENG Feng-xiang(Institute of Medical Information/Medical Library,Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100020,China;School of Public Health Jilin University,Changchun 130021,Jilin Province,China)
出处
《中华医学图书情报杂志》
CAS
2022年第5期72-80,共9页
Chinese Journal of Medical Library and Information Science
基金
中国医学科学院中央级公益性科研院所基本科研业务项目“院校数字医学文献资源建设研究”(2021-YJ630-001)。
关键词
在线健康社区
用户画像
个性化服务
社群化服务
Online health community
User portrait
Personalized service
Community-based service
