The Influence of User Profile and Post Metadata on the Popularity of Image-Based Social Media: A Data Perspective

In modern internet communication, social media platforms have emerged as indispensable tools for self-expression, social engagement, and content distribution. Nevertheless, existing research on predicting social media popularity tends to over-look the complex interactions between different characteristics of user profiles, such as geolocation and account type, and post metadata, such as postdate and hashtags. This paper addresses this gap by investigating the factors derived from user profiles and post metadata contributing to content popularity within social media environments, with a specific emphasis on image-sharing. Utilizing a comprehensive dataset, we employ artificial intelligence-based data analytics techniques to uncover patterns, correlations, and predictive models, thereby providing a detailed insight into the dynamics of popularity within these online spaces.