期刊论文

Research on User Information Requirement in Chinese Network Health Community:Taking Tumor-forum Data of Qiuyi as an Example

中文

数据分析与知识发现

2096-3467

2019

3

4

22-32

10.11925/infotech.2096-3467.2018.1153

教育部人文社会科学重点研究基地重大项目“大数据资源的挖掘与服务研究——面向医疗健康领域”（项目编号:17JJD870002）;教育部规划基金项目“基于前景理论的信息搜索过程建模与预测研究”（项目编号:18YJA870002）的研究成果之一；

本校为其他机构

[目的]构建适应大数据环境的中文网络健康社区用户信息需求挖掘框架,以肿瘤科为例分析用户信息需求.[方法]使用潜在语义索引(LSI)模型和MapReduce分布式文本聚类技术对中文网络健康社区——求医网肿瘤板块的全部提问数据(共计24 305条)进行用户信息需求挖掘.[结果]挖掘出用户的5个信息需求类目及其占比:治疗(43.3％)、病理及病因(34.5％)、检查(12.1％)、术后(7.0％)、预防(3.1％),各类目下Top20关键词;发现国内外各需求类目占比差异巨大;预防信息需求将持续上升;需求的性别差异显著,男性最关注治疗信息、女性最关注病理及病因信息;需求的年龄差异较大,青年群体占比极高(83.79％)等.[局限]可能存...

[Objective] This paper constructs an information demand mining framework of Chinese online health community users adapted to the big data environment,and analyzes the user information needs by taking the data of tumor-forum as an example.[Methods] The Latent Semantic Indexing (LSI) model and MapReduce distributed text clustering technology were used in this framework to mine the user information needs.We use all the Q&A data (24,305 in total) from tumor-forum of Chinese online health community (qiuyi.cn) as the experimental data source.[Results] The proposed framework mines the five informatio...