Information Diffusion and External Influence in Networks

TL;DR

This paper introduces a model for information diffusion in social networks that accounts for both network-based and external influences, applied to Twitter data to quantify their relative impacts.

Contribution

It develops an efficient parameter fitting method for the model and demonstrates how external influences significantly affect information spread in social media.

Findings

Approximately 71% of information in Twitter is due to network diffusion.

External influences account for about 29% of information spread.

Information often 'jumps' across the network, indicating external effects.

Abstract

Social networks play a fundamental role in the diffusion of information. However, there are two different ways of how information reaches a person in a network. Information reaches us through connections in our social networks, as well as through the influence of external out-of-network sources, like the mainstream media. While most present models of information adoption in networks assume information only passes from a node to node via the edges of the underlying network, the recent availability of massive online social media data allows us to study this process in more detail. We present a model in which information can reach a node via the links of the social network or through the influence of external sources. We then develop an efficient model parameter fitting technique and apply the model to the emergence of URL mentions in the Twitter network. Using a complete one month trace of Twitter we study how information reaches the nodes of the network. We quantify the external influences over time and describe how these influences affect the information adoption. We discover that the information tends to "jump" across the network, which can only be explained as an effect of an unobservable external influence on the network. We find that only about 71% of the information volume in Twitter can be attributed to network diffusion, and the remaining 29% is due to external events and factors outside the network.