Mathematical Optimization for Analyzing Performance Metrics of Facebook Posts

In today’s rapidly evolving age, the incorporation of innovative technologies has become an everyday occurrence in various aspects of life worldwide. Therefore, it is crucial to keep up with cutting-edge technology to achieve success in terms of performance. In this article, we have adopted a scientific and technical approach to examine the performance measures of posts published on a brand’s Facebook page, utilizing multi-objective mathematical optimization. We analyzed twelve performance indicators of Facebook posts from a page containing 500 posts and applied Support Vector Regression (SVR) to find the relationship between 7 inputs and 12 outputs. The results obtained reveal how each of the seven input factors affects the desired outcomes. The results presented in this article can assist in guiding management decisions regarding the content and timing of Facebook posts. This research not only aids in formulating improved strategies and management decisions for the publication of Facebook posts but also provides managers with a scientific and technical understanding of how different input variables impact the final performance. This knowledge enhances efficiency and effectiveness in utilizing social media as a strategic tool for advertising and brand management.