|Authors||D. T. Schroeder, J. Langguth, L. Burchard, K. Pogorelov and P. G. Lind|
|Title||The connectivity network underlying the German’s Twittersphere: a testbed for investigating information spreading phenomena|
|Project(s)||UMOD: Understanding and Monitoring Digital Wildfires, Enabling Graph Neural Networks at Exascale|
|Publication Type||Journal Article|
|Year of Publication||2022|
|Publisher||Nature Publishing Group|
Online social networks are ubiquitous, have billions of users, and produce large amounts of data. While platforms like Reddit are based on a forum-like organization where users gather around topics, Facebook and Twitter implement a concept in which individuals represent the primary entity of interest. This makes them natural testbeds for exploring individual behavior in large social networks. Underlying these individual-based platforms is a network whose “friend” or “follower” edges are of binary nature only and therefore do not necessarily reflect the level of acquaintance between pairs of users. In this paper,we present the network of acquaintance “strengths” underlying the German Twittersphere. To that end, we make use of the full non-verbal information contained in tweet–retweet actions to uncover the graph of social acquaintances among users, beyond pure binary edges. The social connectivity between pairs of users is weighted by keeping track of the frequency of shared content and the time elapsed between publication and sharing. Moreover, we also present a preliminary topological analysis of the German Twitter network. Finally, making the data describing the weighted German Twitter network of acquaintances, we discuss how to apply this framework as a ground basis for investigating spreading phenomena of particular contents.