HARNESSING THE HETEROGENEOUS BASS MODEL FOR ACCURATE TWEET POPULARITY FORECASTING

Abstract

In the age of social media, understanding and predicting tweet popularity is crucial for businesses, marketers, and influencers seeking 
to engage effectively with their audience. This paper presents a novel approach to tweet popularity forecasting by leveraging the 
Heterogeneous Bass Model (HBM), a dynamic and well-established framework in marketing that models the diffusion of innovations. By applying the HBM, we aim to capture the influence of both external factors (such as media coverage, hashtag trends, and social events) and internal factors (such as user interactions and content characteristics) on tweet virality.