Structure and Dynamics of Information Pathways in Online Media

TL;DR

This paper presents a novel online algorithm for inferring dynamic, unobserved networks from information diffusion data, revealing insights into how online media pathways evolve during major events.

Contribution

We develop an efficient stochastic convex optimization algorithm for real-time inference of changing networks from diffusion data, applied to large-scale online media analysis.

Findings

Information pathways are more stable for recurrent topics than for ongoing news.

Clusters of media sites emerge and vanish rapidly during news events.

Major social movements increase information pathways and network centrality of blogs.

Abstract

Diffusion of information, spread of rumors and infectious diseases are all instances of stochastic processes that occur over the edges of an underlying network. Many times networks over which contagions spread are unobserved, and such networks are often dynamic and change over time. In this paper, we investigate the problem of inferring dynamic networks based on information diffusion data. We assume there is an unobserved dynamic network that changes over time, while we observe the results of a dynamic process spreading over the edges of the network. The task then is to infer the edges and the dynamics of the underlying network. We develop an on-line algorithm that relies on stochastic convex optimization to efficiently solve the dynamic network inference problem. We apply our algorithm to information diffusion among 3.3 million mainstream media and blog sites and experiment with more than 179 million different pieces of information spreading over the network in a one year period. We study the evolution of information pathways in the online media space and find interesting insights. Information pathways for general recurrent topics are more stable across time than for on-going news events. Clusters of news media sites and blogs often emerge and vanish in matter of days for on-going news events. Major social movements and events involving civil population, such as the Libyan's civil war or Syria's uprise, lead to an increased amount of information pathways among blogs as well as in the overall increase in the network centrality of blogs and social media sites.