With the development of technology, the use of social platforms is becoming more and more common. People have very different views on social media, some think it is a good tool to help us maintain social interaction, while, others think that social media has too many negative effects that weigh out its positive effects. College students are a large part of the population that uses social media. In this paper, the author uses a literature study to investigate the previous literature and tries to find the relationship between college students' social media use and their anxiety level. The study aims to help the college student population address social anxiety-related issues. The results of the study did not find a strong positive or negative relationship between social media use and anxiety level among college students. However, the study found that the three negative effects of social media use did increase social anxiety levels among college students.

A dynamic reconfiguration method based on the improved multi-objective dung beetle optimizer (IMODBO) is proposed to reduce the operating cost of the distribution network with distributed generation (DG) and ensure the quality of the power supply, while also minimizing the number of switch operations during dynamic reconfiguration. First, a multi-objective model of distribution network dynamic reconfiguration with the optimization goal of minimizing active power loss and voltage deviation is established. Secondly, the K-means++ clustering algorithm is used to divide the daily load of the distribution network into periods. Finally, using the IMODBO algorithm, the distribution network is reconstructed into a single period. The IMODBO algorithm uses the chaotic tent map to initialize the population, which increases the ergodicity of the initial population and solves the problem of insufficient search space. The algorithm introduces an adaptive weight factor to solve the problem of the algorithm easily falling into a locally optimal solution in the early stage with weak searchability in the later stage. Levy flight is introduced in the perturbation strategy, and a variable spiral search strategy improves the search range and convergence accuracy of the dung beetle optimizer. Reconfiguration experiments on the proposed method were conducted using a standard distribution network system with distributed power generation. Multiple sets of comparative experiments were carried out on the IEEE 33-nodes and PG&E 69-nodes. The results demonstrated the effectiveness of the proposed method in addressing the multi-objective distribution network dynamic reconfiguration problem.