This study focuses on the application of big data technology in party discipline education in universities,exploring its contribution in enhancing the personalization,modernization,precision,and maxi-mizing the effectiveness of party discipline education.By constructing a database of party member behavior and using the cross linked list analysis method,this study conducts an in-depth analysis of the behavioral characteristics of university party members and explores customized party discipline education strategies based on this.Research has found that through quantitative and qualitative analysis of the party discipline learning situation of faculty and party members,the application of big data technology can significantly im-prove the pertinence and effectiveness of party discipline education,especially in enhancing the discipline awareness of party members.Due to the small sample size,it may affect the broad applicability of the conclu-sions,and there is a lack of continuous tracking on the long-term effects and deep impacts of big data tech-nology in party discipline education.In the future,the sample size will be expanded to explore in depth the long-term application effects of big data technology in party discipline education,as well as the ethical and legal issues that may arise.This study provides a new perspective for the party building work in universities,and has important theoretical and practical value for cultivating socialist builders and successors with an in-ternational perspective.
Party Building in UniversitiesBig DataAnalysis of Party Member BehaviorParty Disci-pline EducationCustomization
NETL
NSTL
万方数据
