 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 which tasks should be scheduled together. This ensures that tasks do not conflict with one another while still allowing for efficient use of resources. The algorithm was tested using real-world data sets and showed significant improvements over existing algorithms. This article was authored by Weina Fu, Shwailu and Gautam Shrivastava.