基于BTM模型的医务人员遭受网络暴力公众评论的主题分析

Thematic Analysis of Public Comments on Cyber Violence Against Medical Professionals Based on the Bi-term Topic Model

目的:了解自媒体平台关于医务人员遭受网络暴力事件的公众评论主题,探究公众关注热点,为促进医患关系,保护医务人员心理健康,维护良好网络秩序提供参考。方法:使用Python软件爬取自媒体平台用户发布的评论,采用RostCM6.0软件进行词频分析和语义网络分析,采用Python语言编程实现BTM模型,对医务人员遭受网络暴力事件中公众评论进行主题挖掘。结果:经爬取、筛选后共获得1212条自媒体评论。BTM主题分析得出8个主题,主题聚类分析得出“信息发布与传播”“对事件当事人的评论”“对事件的建议与评价”3个主题。结论:自媒体平台中涉医网络暴力不单指向医务人员,更涉及负向典论的传播与扩散,其表象之下是对医患关系与医疗秩序的破坏。相关部门应持续关注媒体及网民动向,并加强网络平台监管技术与责任,宣传医患和谐共处,谨防不良情感信息传播的负向影响。

Objective To understand the themes of public comments on self-media platforms about cyber violence against medical personnel,explore the hotspots of public concern,and provide references for promoting doctor-patient relationship,pro-tecting the mental health of medical personnel,and maintaining a good network order.Methods The comments posted by users on self-media plaforms was crawled by Python software,word frequency analysis and semantic network analysis were made by using Rost CM 6.O software,and the BTM model was implemented by using Python programming,from which the themes of public com-ments on cyber-violence incidents against medical personnel were obtained.Results A total of 1212 self-media comments were obtained after crawling and screening.Eight themes were obtained by BTM theme analysis,and three themes were obtained in"in-formation release and dissemination","comments on the parties involved in the incident",and"suggestions and evaluation of the incident"by using theme clustering analysis.Conclusion Medical cyberviolence in the self-media platforms is not only directed at medical personnel,but also involves the dissemination and diffusion of negative public opinion,underneath the surface of which is the destruction of doctor-patient relationship and medical order.Relevant departments should pay close attention to the media and netizens,and strengthen the monitoring technology and responsibility of online platforms,so as to promote harmonious coexistence between doctors and patients,and prevent the negative impact of the spread of undesirable emotional information.