Information Contagion: an Empirical Study of the Spread of News on Digg and Twitter Social Networks

TL;DR

This study empirically analyzes how news spreads on Digg and Twitter, revealing the significant influence of social network structures on information dissemination dynamics.

Contribution

It provides the first direct analysis of real social network structures and their impact on news spread on Digg and Twitter.

Findings

Social networks significantly influence news spread.

Network structure affects information flow dynamics.

Empirical data shows rapid dissemination through social ties.

Abstract

Social networks have emerged as a critical factor in information dissemination, search, marketing, expertise and influence discovery, and potentially an important tool for mobilizing people. Social media has made social networks ubiquitous, and also given researchers access to massive quantities of data for empirical analysis. These data sets offer a rich source of evidence for studying dynamics of individual and group behavior, the structure of networks and global patterns of the flow of information on them. However, in most previous studies, the structure of the underlying networks was not directly visible but had to be inferred from the flow of information from one individual to another. As a result, we do not yet understand dynamics of information spread on networks or how the structure of the network affects it. We address this gap by analyzing data from two popular social news sites. Specifically, we extract social networks of active users on Digg and Twitter, and track how interest in news stories spreads among them. We show that social networks play a crucial role in the spread of information on these sites, and that network structure affects dynamics of information flow.