Article
Version 1
This version is not peer-reviewed
Interaction Strength Analysis to Model Retweet Cascade Graphs
Version 1
: Received: 13 October 2020 / Approved: 14 October 2020 / Online: 14 October 2020 (08:23:40 CEST)
A peer-reviewed article of this Preprint also exists.
Zola, P.; Cola, G.; Mazza, M.; Tesconi, M. Interaction Strength Analysis to Model Retweet Cascade Graphs. Appl. Sci. 2020, 10, 8394. Zola, P.; Cola, G.; Mazza, M.; Tesconi, M. Interaction Strength Analysis to Model Retweet Cascade Graphs. Appl. Sci. 2020, 10, 8394.
Abstract
Tracking information diffusion is a non-trivial task and it has been widely studied across different domains and platforms. The advent of social media has led to even more challenges, given the higher speed of information propagation and the growing impact of social bots and anomalous accounts. Nevertheless, it is crucial to derive a trustworthy information diffusion graph, which is capable of highlighting the importance of specific nodes in spreading the original message. The paper introduces the interaction strength, a novel metric to model retweet cascade graphs by exploring users’ interactions. Initial findings show the soundness of the approaches based on this new metric with respect to the state-of-the-art model, and its ability to generate a denser graph, revealing crucial nodes that participated in the retweet propagation. Reliable retweet graph generation will enable a better understanding of the diffusion path of a specific tweet.
Keywords
social media; network analysis; interaction strength; retweet graph; retweet cascade
Subject
Computer Science and Mathematics, Computer Vision and Graphics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
