Modeling brand post popularity dynamics in online social networks

Today's social media platforms are excellent vehicles for businesses to build and foster relationship with customers. Companies create official fan pages on social network websites to provide customers with information about their brands, products, promotions, and more. Customers can become fans of these pages, and like, reply, share or mark the brand post as favorite. Marketing departments are using these activities to crowdsource marketing and increase brand awareness and popularity. Understanding how crowdsourcing oriented marketing and promotion evolves would be helpful in managing such campaigns. In this paper, we adopt a multidimensional point process methodology to study crowd engagement activities and interactions. Specifically, we investigate the brand post popularity as a joint probability function of time and number of followers. One-dimensional and two-dimensional Hawkes point process models are calibrated to simulate popularity growth patterns of brand post contents on Twitter. Our results suggest that the two-dimensional point process model provides a good model for understanding such crowdsourcing behavior.