摘要
[目的/意义]基于健康码的社会治理模式引发了不少社会治理问题。为了帮助健康码设计者和相关政府部门了解基于健康码的社会治理模式存在的实际问题以及用户对于该社会治理模式的迫切需求,并且为今后健康码的优化以及其他以数据为基础的社会治理模式提供参考,本文针对健康码的相关社会治理问题展开了研究。[方法/过程]本文选取新浪微博平台为实验对象,通过采集新浪微博上有关健康码话题的文本数据,利用利益相关者理论、基于聚集策略的LDA模型对微博数据进行了利益相关者划分和健康码主题建模。[结果/结论]本文借鉴利益相关者理论识别划分了8类利益相关者群体,同时采用基于聚集策略的LDA模型对不同类型的利益相关者的微博推文进行主题建模,总结出4类基于健康码的社会治理问题,并挖掘了不同利益相关者对基于健康码的社会治理关注差异及其随时间的变化趋势,针对重点问题提出一些健康码优化的对策建议。
[Purpose/significance]The social governance model based on the COVID-tracking codes has caused many social governance problems.In order to help COVID-tracking codes designers and relevant government departments understand the practical problems of the COVID-tracking codes-based social governance model and the urgent needs of users for this social governance model,and to optimize the COVID-tracking codes and other data-based social governance models in the future for reference,this paper conducts research on social governance issues related to COVID-tracking codes.[Method/process]This paper selects Sina Weibo platform as the experimental object,collects text data on COVID-tracking codes topics on Sina Weibo,uses stakeholder theory and LDA model based on aggregation strategy to conduct stakeholder analysis on Weibo data.Partitioning and topic modeling of COVID-tracking codes.[Result/conclusion]In this paper,8 types of stakeholder groups are identified and divided into 8 types of stakeholder groups based on stakeholder theory,and the LDA model based on aggregation strategy is used to model the microblog tweets of different types of stakeholders,and 4 types of stakeholder groups are summarized.Based on the social governance issues of COVID-tracking codes,and excavated the differences in the attention of different stakeholders to social governance based on COVID-tracking codes and their changing trends over time,some countermeasures and suggestions for COVID-tracking codes optimization are put forward for key issues.
作者
邓胜利
王泽鑫
Deng Shengli;Wang Zexin(Center for the Studies of Information Resources of Wuhan University,Hubei,430072)
出处
《情报资料工作》
CSSCI
北大核心
2022年第2期36-45,共10页
Information and Documentation Services
基金
国家自然科学基金项目“信息生态链视角下在线知识社区用户贡献行为评价及预测研究”(批准号:71974149)的研究成果。
关键词
健康码
利益相关者
LDA模型
社会治理关注
主题演化
COVID-tracking codes
stakeholders
LDA model
social governance concerns
theme evolution