The Dynamics of Retweeting on Twitter

In this work we analyze the dynamics retweeting in the micro-blogging site Twitter. We propose a model for Twitter users' retweeting behavior which incorporates two key elements: the arrival patterns of users to Twitter and the design of the Twitter user interface. Using only these elements, our model predicts a distribution of user retweet times which agrees with observations on over 2.4 million retweets in Twitter. Our model allows us to predict the probability of a tweet being viewed by a specific user and the impact of promotional activity on the visibility of a tweet. This suggests that our model can serve as a tool to optimize advertising services provided by Twitter which promote tweets.
Tauhid Zaman is an Assistant Professor of Operations Management at the MIT Sloan School of Management. His research focuses on utilizing large-scale data from online social networks such as Facebook and Twitter to develop predictive models for user behavior and enhance business operations. He received his BS, MEng, and PhD degrees in electrical engineering and computer science from MIT. Before returning to MIT he spent one year as a postdoctoral researcher in the Wharton Statistics Department at the University of Pennsylvania. His work has been featured in Wired, Mashable, the LA Times, and Time Magazine.