The Statistical Mechanics of Twitter

Abstract

In this thesis I aim to show that many properties of online social communities can be described using the language of statistical physics. I first elucidate how the statistics of language used online suggest a simplification for social media data that captures many important features of activity on social networks. I characterize this simplified data and I then build models that describe essential features of the social data. Features of these models, as well as statistical features of the data independent of inferring models, indicate that these social systems are poised at the analogue of a critical point in a physical system. I then explore the implications of this fact and possible uses for the results presented here.