Enhancing Social Media Post Popularity Prediction with Visual Content

arXiv:2405.02367v1 Announce Type: new
Abstract: Our study presents a framework for predicting image-based social media content popularity that focuses on addressing complex image information and a hierarchical data structure. We utilize the Google Cloud Vision API to effectively extract key image and color information from users' postings, achieving 6.8\% higher accuracy compared to using non-image covariates alone. For prediction, we explore a wide range of prediction models, including Linear Mixed Model, Support Vector Regression, Multi-layer Perceptron, Random Forest, and XGBoost, …

abstract accuracy api arxiv cloud color cs.cv cs.lg data extract framework google google cloud hierarchical image information key media prediction social social media study type vision visual