[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 codesbased 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 so? cial 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 aggrega? tion 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 sugges? tions for COVID-tracking codes optimization are put forward for key issues.