图书情报知识 ›› 2023, Vol. 40 ›› Issue (3): 116-128.doi: 10.13366/j.dik.2023.03.116

• 情报、信息与共享 • 上一篇    下一篇

融入信息推荐场景要素的在线健康社区用户画像研究

夏立新, 胡畔, 刘坤华, 翟姗姗   

  1. 华中师范大学信息管理学院,武汉,430079
  • 出版日期:2023-05-10 发布日期:2023-06-25
  • 通讯作者: 胡畔(ORCID:0000-0002-3916-5457),博士研究生,研究方向:信息组织与检索,Email:1160708724@qq.com。
  • 作者简介:夏立新(ORCID:0000-0002-4162-2282),博士,教授,研究方向:信息组织与检索、知识管理服务,Email:xialx@ccnu.edu.cn;刘坤华(ORCID:0000-0002-6196-7923),本科生,研究方向:信息组织与检索,Email:huask25069@163.com;翟姗姗(ORCID:0000-0002-2787-0183),博士,教授,研究方向:信息检索与组织,Email:zhais@ccnu.edu.cn。
  • 基金资助:
    本文系国家社科基金重大项目“新时代我国文献信息资源保障体系重构研究”(19ZDA345)和华中师范大学优秀博士学位论文培育项目“总体国家安全观视阈下的科技文献信息资源保障研究”(2022YBZZ058)的研究成果之一。

User Portrait of Online Health Communities Integrating Information Recommendation Scenario Elements

XIA Lixin, HU Pan, LIU Kunhua, ZHAI Shanshan   

  1. School of Information Management, Central China Normal University, Wuhan,430079
  • Online:2023-05-10 Published:2023-06-25
  • Contact: Correspondence should be addressed to HU Pan, Email:1160708724@ qq.com, ORCID: 0000-0002-3916-5457
  • Supported by:
    This is an outcome of the Major Project "Research on the Reconstruction of Literature Information Resources Guarantee System in China in the New Era"(19ZDA345)supported by National Social Science Foundation of China and the project"Research on the Guarantee of Scientific and Technological Literature Information Resources from the Perspective of Holistic National Security"(2022YBZZ058)supported by a grant from Excellent Doctoral Dissertation Cultivation Program of Central China Normal University.

摘要: [目的/意义]旨在提高在线健康社区信息服务水平,满足患者用户不同场景下的深层次信息需求。[研究设计/方法]融入信息推荐服务的场景要素,通过分析在线健康社区用户信息需求,确定场景划分标准继而划分推荐场景,从而识别不同场景要素标签,构建用户画像概念模型,并采用 RFM模型对采集到的在线健康社区用户数据进行精细化筛选运营,借助形式概念分析的方法实现在线 健康社区用户画像模型构建,并以“甜蜜家园”为数据源实现糖尿病在线健康社区用户画像构建和标签聚类。[结论/发现]通过深度挖掘聚类,发现在线健康社区“观望型”“宣传型”“高产型”和“经验型”四类用户群体及其健康信息需求。[创新/价值]以信息推荐服务模式为导向,聚焦于用户画像构建的整体流程,此研究视角有助于在线健康社区优化服务水平,提升用户满意度。

关键词: 用户画像, 在线健康社区, 信息推荐, 场景要素

Abstract: [Purpose/Significance] The purpose of this study is to improve the information service level of online health community and meet the deep information needs of patients and users in different scenarios. [Design/Methodology] Integrated the scenario elements of information recommendation service, based on the analysis of the information needs of users in the online health community, the scenario division criteria were determined and then the recommendation scenarios were divided, so as to identify different scenario element labels to build a user portrait conceptual model. By RFM model, the user data of the online health communities were refined and operated, and the user portrait model of the chronic disease online health community was constructed by means of the method of formal concept analysis. In addition, "Sweet Homeland" was used as the data source to realize the user portrait construction and label clustering of diabetes online health community. [Findings/Conclusion] Through in-depth mining and clustering, this paper finds four types of user groups and their health information needs namely "wait-and-see","propagandistic","prolific" and "experience". [Originality/Value] Under the guidance by the information recommendation service model, this paper focuses on the overall process of user portrait construction, which is helpful to optimize the service level of online health community and improve user satisfaction.