 This paper proposes an optimized scheduling algorithm for social network big data. The algorithm considers both the amount of data communication between tasks and the amount of data processing required by each task when determining the optimal schedule. This ensures that tasks with high priority are completed first while minimizing the total execution time. The experimental results demonstrate that the proposed algorithm can quickly optimize the scheduling of social network data and effectively solve the problem of strong data collision. This article was authored by Weina Fu, Shwailu, and Gautam Srivastava.