Analyzing interactions in donation-based live streaming platforms: a multi-leader-follower game approach

This paper investigates the interactions between content creators and viewers in donation-based live streaming platforms. In these social media systems, creators produce their content, while viewers enjoy the live streaming and decide to donate money to creators, making decisions to contribute financial support to the creators. To capture the sequential decision process of the model, we introduce a multi-leader-follower game, in which creators act as the leaders of the game and viewers as the followers. Creators first optimize their performance level and the duration of the streams to maximize their profit. Then, viewers optimize the time spent watching a live stream to maximize their utility. Thus, the first stage of the game models the non-cooperative competition among creators, while the second stage represents the behaviour of viewers deciding on their content demands. We formulate these stages as Nash equilibrium problems, and then as variational inequalities. We analyze the existence and uniqueness of the Stackelberg equilibrium. Then, we derive a supervised learning algorithm to estimate the parameters of the Artificial Neural Network model, focused on the advertisement function to properly verify the proposed model in a realistic setting.