Is Your Time Well Spent Online?: Focusing on Quality Experiences Through a User-Centered Recommendation Algorithm and Simulation Model

Spending an uncontrolled quantity and quality of time on digital news and social media platforms can negatively influence mental health and decrease cognitive abilities. In this paper, we propose a sequential news recommendation system employing deep reinforcement learning to capture the user’s short and long-term interests while blending social news with micro-learning informative news items that can help users derive useful outcomes out of their online presence. In the absence of a publicly available dataset, we developed a simulation model to synthesize data and evaluate the proposed news recommendation system. We train and evaluate our model on synthesized data and show an improvement in user satisfaction.