Existence of outsiders as a characteristic of online communication networks

TL;DR

This paper investigates Twitter communication networks and identifies a small group of outsiders who connect different user groups without forming their own, highlighting a structural feature that impacts social network analysis.

Contribution

The study introduces the concept of outsiders in online social networks and develops a method to identify them by optimizing network assortativity.

Findings

Outsiders are connected to multiple groups but not well connected among themselves.

Identified outsiders are consistent with the hypothesis based on structural analysis.

The presence of outsiders affects the interpretation of online social network structures.

Abstract

Online social networking services (SNSs) involve communication activities between large number of individuals over the public Internet and their crawled records are often regarded as proxies of real (i.e., offline) interaction structure. However, structure observed in these records might differ from real counterparts because individuals may behave differently online and non-human accounts may even participate. To understand the difference between online and real social networks, we investigate an empirical communication network between users on Twitter, which is perhaps one of the largest SNSs. We define a network of user pairs that send reciprocal messages. Based on the mixing pattern observed in this network, we argue that this network differs from conventional understandings in the sense that there is a small number of distinctive users that we call outsiders. Outsiders do not belong to any user groups but they are connected with different groups, while not being well connected with each other. We identify outsiders by maximizing the degree assortativity coefficient of the network via node removal, thereby confirming that local structural properties of outsiders identified are consistent with our hypothesis. Our findings suggest that the existence of outsiders should be considered when using Twitter communication networks for social network analysis.