SoMeMax - A Novel AI-driven Approach to Generate Artificial Social Media Content That Maximises User Engagement

Abstract

Today, many artificial or virtual influencers roam social media platforms to maximise followers and offer commercial options for companies. This work focuses on developing artificial influencers using state-of-the-art techniques within deep learning. Specifically, an autonomous theoretical framework for generating social media content that maximises user engagement is proposed. Deep learning models for generating realistic images and hashtags are trained on a dataset from a social media platform, and content is optimised for user engagement using an evolutionary algorithm. The generated images were evaluated by participants from existing social media users through two separate surveys. The complete framework is built, trained, and tested, and functionality is confirmed. The framework, which appears to be the first of its kind, produces content that matches the users' preferences well.