Interaction Strength Analysis to Model Retweet Cascade Graphs

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 that 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 showed 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

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Author Zola, Paola
Author Cola, Guglielmo guglielmo.cola@iit.cnr.it
Author Mazza, Michele
Author Tesconi, Maurizio
DOI https://doi.org/10.3390/app10238394
Group Societal Debates
Publisher Applied Sciences
Source Appl. Sci. 2020, 10(23), 8394
Thematic Cluster Social Network Analysis [SNA]
system:type JournalArticle
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Author Wright Joanna
Maintainer Guglielmo Cola
Version 1
Last Updated 5 March 2021, 12:45 (CET)
Created 16 February 2021, 11:11 (CET)