Nothing But Net? Content and Network Factors in Information Diffusion

שלחו לחבר
Oren Tsur
Engineering Building 1103, Room 329
Harvard University and Northeastern University

Information diffusion is the process in which nuggets of information spread in a network (typically a social network). This is a complex process that depends on the network topology, the social structures and the information itself (content/language). In this talk I will discuss information diffusion from these different yet complementary perspectives. In the first part  of the talk I will focus on the features of the diffusing information.  I will  present a gradient boosted trees algorithm modified for learning user preferences of Twitter hashtags. In the second part of my talk I will focus on the network structure. I will use exponential random graph models (ERGM) in order to learn what latent factors contribute to network formation and I will show how network structure and social roles contribute to the information spread. Specifically, I will present promising results obtained on political networks in the American political systems and analysis of the partisan use of political hashtags. 

In both parts I put emphasis on interpretable models that go beyond accurate prediction and  facilitate a better understanding of complex social processes.