An Analysis of the Dynamics of Ties on Twitter

Published: 01 Jan 2023, Last Modified: 27 Jan 2025IEEE Big Data 2023EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Online social networks are the breeding grounds for user connections, fostering information exchange, communication, content sharing, and community building. However, the dissolution of these digital relationships, often a less-explored facet, complements the studies of tie formation and maintenance. A comprehensive grasp of these connections, encompassing their inception, unraveling, and the potential foresight of disconnections, offers invaluable insights into network dynamics and the progression of interpersonal bonds. Yet, the investigation of broken ties faces a substantial challenge: the paucity of longitudinal and detailed data. To bridge this gap, this paper curates an expansive dataset, spanning over 120,000 Twitter users tracked across 15 weeks with weekly snapshots. Armed with this dataset, we embark on an extensive exploration of Twitter links, delving into five distinct categories within the Twitter social graph. These categories encompass structural features like centrality, content-related aspects, including post polarity, user profile attributes like verified status, egocentric network elements such as reciprocity, and dense user representations typified by node2vec. Subsequently, we conduct a thorough analysis of these diverse features to unveil meaningful patterns.
Loading