Modelling cascade formation in Twitter amidst mentions and retweets

This paper presents an analytical framework for cascade formation considering both retweet and mentioning activities into account. We introduce two mention strategies (a) random mention and (b) smart mention to model the mention preferences of the users. The proposed framework analytically computes the cascade size, depicting tweet popularity and discovers the presence of a critical retweet rate, under which mentioning in a tweet significantly helps in cascade formation. We validate the proposed framework with the help of Monte-Carlo simulation; we demonstrate the generality of the framework taking both empirical and synthetic follower networks into consideration. This framework proves the elegance of smart mention strategy, in boosting tweet popularity, specially in the low retweeting environment.