摘要

 With the rapid development of the Internet, the network behavior of college students presents diversified characteristics, especially the problems of internet addiction, information leakage and online learning dependence are increasingly prominent. These behaviors have a far-reaching impact on students' studies, mental health and social interaction, so it is particularly important to optimize the network behavior management strategy and establish an effective risk prevention and control mechanism. Based on the analysis of the current situation of college students' network behavior, this study discusses their behavior characteristics and potential risks, evaluates the effect of existing management measures, and puts forward optimization strategies. It is found that strategies such as information literacy education, mental health intervention and behavior monitoring mechanism have positive effects in management practice, but there is still the problem of uneven implementation effect. This study further discusses the application of emerging technologies in network behavior management, big data and artificial intelligence, so as to improve the personalization and accuracy of management strategies. The research suggests that the multi-dimensional risk prevention and control mechanism and policy system should be established to strengthen the synergy among schools, families and the government, so as to realize the all-round management of students' online behavior. This study provides a new theoretical basis and practical guidance for the management of network behavior in colleges and universities.