Working Paper Article Version 1 This version is not peer-reviewed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)

How to cite: Zola, P.; Cola, G.; Mazza, M.; Tesconi, M. Interaction Strength Analysis to Model Retweet Cascade Graphs. Preprints 2020, 2020100289 Zola, P.; Cola, G.; Mazza, M.; Tesconi, M. Interaction Strength Analysis to Model Retweet Cascade Graphs. Preprints 2020, 2020100289

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.

Subject Areas

social media; network analysis; interaction strength; retweet graph; retweet cascade

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