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基于知乎抑郁症问答社区的用户健康 信息需求分析.

Objective：To analyze users' needs on health information in Zhihu Q &A community, in order to optimize models of health information service and provide a basis for personalized information service for depression healthcare. Methods：Python was used to crawl the question records on the topic of depress...

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Publicado en:Chinese Nursing Research Vol. 35; no. 13; pp. 2273 - 2280
Autores principales: 刘烁, 陈盼, 杨冰香, 付光晖, 马跃, 王瑞乾, 沈奥, 黄润
Formato: research tables/charts Journal Article
Publicado: Chinese Nursing Research Editorial Office Jul2021
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: Chinese Nursing Research
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      dt: Jul2021
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      pub: Chinese Nursing Research Editorial Office
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        10.12102/j.issn.1009-6493.2021.13.003
        151448543
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        atl: 基于知乎抑郁症问答社区的用户健康 信息需求分析.
      aug:
        au:
          刘烁
          陈盼
          杨冰香
          付光晖
          马跃
          王瑞乾
          沈奥
          黄润
        affil: 武汉大学健康学院, 湖北430071
      sug:
        subj:
          Consumer Health Information
          Information Needs
          World Wide Web
          Information Services
          Depression Prevention and Control
          Human
          Descriptive Statistics
          Data Analysis Software
          Cluster Analysis
          Algorithms
          China
      ab:
        Objective：To analyze users' needs on health information in Zhihu Q &A community, in order to optimize models of health information service and provide a basis for personalized information service for depression healthcare. Methods：Python was used to crawl the question records on the topic of depression in of Zhihu Q &A community. K-means clustering analysis was used to classify the hot question records in all questions. Jieba tool was used to divide words, and the top 100 high frequency keywords were calculated using a TF-IDF algorithm. Gephi software was used to visually analyze the co-occurrence matrix of high frequency keywords. Results：A total of 685 hot question records were included in all questions. The clustering analysis showed that questions about depression could be classified into four categories, which were basic knowledge, social life, prevention and self-management, and education. Basic knowledge included the causes of depression, symptoms, diagnosis and discrimination, treatment, and complications. Social life included social contact, social evaluation and depression related video and audio. Conclusion：Based on the diversity of health information needs in question-and-answer communities, it was suggested that the classification and identification of user roles should be optimized. And targeted and personalized health information service should be considered for users with different subjects when carrying out depression health information services.
        目的:分析知乎抑郁症问答社区用户的健康信息需求, 以优化健康信息服务模式, 为制定个性化的抑郁症健康信息服务提供 决策依据。方法:使用Python 爬取知乎中"抑郁症"话题的提问记录, 利用K-Means 聚类方法归类其中的热点提问记录, 通过分词、 TF-IDF 算法计算排名前100 位的高频关键词, 使用Gephi 软件对关键词的共现矩阵进行可视化分析。结果:爬取的提问内容中包含 685 条热点提问记录。聚类分析结果显示, 抑郁症提问内容可归为四大类：基本知识（包括抑郁症的病理原因、患抑郁症的表现、抑 郁症的诊断与辨别、治疗、并发症）、社会生活类（包括社会交往、社会评价及与抑郁症相关的影视音频）、自我管理及预防类、教育类。 结论:基于问答社区健康信息需求主体的多样性, 提示应优化用户角色的分类识别, 在进行抑郁症健康信息服务时应考虑为不同主 体的用户提供针对性、个性化的健康信息.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: Chinese
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