Abstract
This paper presents a novel Retweet Model for online social networks. The objective is to model retweeting patterns based on historical data of user interactions, inherent topical similarity between tweets reaching the current user and tweets of their top K friends, and the nature of interactions of a user with their neighbours in the social network. Point Processes have recently received significant attention from researchers in social media analytics. We have modelled a Hawkes Process for online social networks to investigate retweeting patterns.
