公众对"陪诊服务"的态度和关注点：基于微博评论的文本挖掘

doi:10.12114/j.issn.1007-9572.2023.0652

摘要/Abstract

摘要： 背景随着人口老龄化程度不断加深，增加异地就医等现实需要以及人们对高品质生活的追求，"陪诊服务"受到了较多的关注。目的基于微博评论数据，采用文本挖掘技术探讨公众对"陪诊服务"的情感态度及关注点。方法以"陪诊服务""陪诊师""陪诊员"为关键词搜索微博（截至2023-04-01）并抓取微博评论，采用"wordcloud"绘制高频词分析的词云图，采用SnowNLP模块分析评论情感倾向，采用狄利克雷分布主题模型获取评论的潜在主题。结果共抓取到2 376条评论，公众对"陪诊服务"的情感得分均值为0.666 6分；主题模型识别出4类潜在主题，分别为服务对象、有偿服务、心理治愈以及未来挑战。结论公众对于"陪诊服务"的总体感情呈现出弱积极性。因此，建议将"陪诊服务"纳入新的职业范畴，并通过培训和认证等措施，将护理人员转化为专业的陪诊师，以确保"陪诊服务"的专业性和规范化。

关键词: 门诊医疗, 陪诊师, 陪诊员, 陪诊服务, 文本挖掘, 态度

Abstract:

Background

With the intensification of population aging and the increasing demand for out-of-place medical treatment, as well as the pursuit of a high-quality life, "patient navigators" have attracted considerable attention.

Objective

This study aims to explore the public's emotional attitudes and concerns about "companion services" based on Weibo comment data using text mining techniques.

Methods

We searched Weibo (up to April 1, 2023) using keywords "companion services" "companion assistants" "companion staff" and collected comments. A "wordcloud" was created to analyze the frequency of keywords, the SnowNLP module was used to analyze the sentiment of the comments, and a Dirichlet distribution topic model was applied to identify latent topics in the comments.

Results

A total of 2 376 comments were collected, with the public's average sentiment score towards "companion services" being 0.666 6. The topic model identified four latent topics: service recipients, remuneration for services, psychological healing, and future challenges.

Conclusion

The public's overall sentiment towards "companion services" exhibits a weakly positive attitude. Therefore, it is recommended to incorporate "companion services" into a new professional category and to transform nursing personnel into professional companions through training and certification measures to ensure the professionalism and standardization of "companion services".

Key words: Ambulatory care, Patient navigators, Attendant, Companion services, Text mining, Attitude

中图分类号:

R 45

杨雅婷,王頔,吴金局,等. 公众对"陪诊服务"的态度和关注点：基于微博评论的文本挖掘[J]. 中国全科医学, 2026, 29(14): 1816-1820. DOI: 10.12114/j.issn.1007-9572.2023.0652.
YANG Yating,WANG Di,WU Jinju, et al. Attitude and Concerns of the Public about "Patient Navigators": a Text Mining Study Based on Weibo Comments[J]. Chinese General Practice, 2026, 29(14): 1816-1820. DOI: 10.12114/j.issn.1007-9572.2023.0652.

图/表 4

图1 高频词词云图

Figure 1 High-frequency word cloud map

图2 所有评论情感得分分布

Figure 2 All reviews sentiment score distribution

表1 部分原始评论及情感得分

Table 1 Some original reviews and sentiment scores

评论内容	情感得分（分）
算是社会需求，无论是老年人还是年轻人，身体不舒服看病都需要陪同	0.999 680
害怕孤独；陪诊师这个职业不错	0.999 532
需要什么门槛吗	0.500 000
社会分工的必然产物	0.517 974
收费标准比较混乱，各自喊价	0.026 869
不少陪诊师兼职都是骗人来交培训费的	0.005 914

图3 主题分布及相应主题最相关的前20个主题词注：A为基于多维尺度分析的主题间距离气泡图，B为各主题最相关的前20个主题词列表；气泡距离越近，相似度越高；距离越远，差异越大。

Figure 3 Topic distribution and the top 20 most relevant topic words

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