A game-theoretic modeling of popularity dynamics

In the big data era, numerous items such as online memes and videos are generated everyday, some of which go viral, i.e., attract lots of attention, while most diminish quickly without any influence. The recorded people's interactions with these items constitute a rich amount of popularity dynamics, e.g., hashtags' mention count dynamics. It is crucial to understand the underlying mechanisms of popularity dynamics in order to utilize the valuable attention of people efficiently. In this work, we propose a game-theoretic model to analyze and understand popularity dynamics. The model takes into account both the instantaneous incentives and long-term incentives during people's decision making process. We analyze the equilibrium of the game and show several properties at the equilibrium, which confirm with the observations from real data. By using simulations as well as experiments based on real-world popularity dynamics data, we validate the effectiveness of the theory. We find that our theory can fit the real data well and can even predict the future dynamics.