Identifying Communication Topologies on Twitter

Kustudić, Mijat and Xue, Bowen and Zhong, Huifen and Tan, Lijing and Niu, Ben (2021) Identifying Communication Topologies on Twitter. Electronics, 10. ISSN 2079-9292

Text 4 Identifying Communication Topologies on Twitter, Electronics.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (2MB)

Abstract

Social networks are known for their decentralization and democracy. Each individual has a chance to participate and influence any discussion. Even with all the freedom, people’s behavior falls under patterns that are observed in numerous situations. In this paper, we propose a method‐ology that defines and searches for common communication patterns in topical networks on Twit‐ter. We analyze clusters according to four traits: number of nodes the cluster has, their degree and betweenness centrality values, number of node types, and whether the cluster is open or closed. We find that cluster structures can be defined as (a) fixed, meaning that they are repeated across da‐tasets/topics following uniform rules, or (b) variable if they follow an underlying rule regardless of their size. This approach allows us to classify 90% of all conversation clusters, with the number varying by topic. An increase in cluster size often results in difficulties finding topological shape rules; however, these types of clusters tend to exhibit rules regarding their node relationships in the form of centralization. Most individuals do not enter large‐scale discussions on Twitter, meaning that the simplicity of communication clusters implies repetition. In general, power laws apply for the influencer connection distribution (degree centrality) even in topical networks.

Actions (login required)

View Item