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Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media
Name
entropy-23-00160.pdf
Size
1.19 MB
Format
Adobe PDF
Checksum (MD5)
43bb180e5e059155ffb850166eba2d0d
Author(s)
Senevirathna, Chathurani
Gunaratne, Chathika
Rand, William
Jayalath, Chathura
Garibay, Ivan
Date Issued
January 28, 2021
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Entropy 23 (2): 160 (2021)
Version
Final published version
Abstract
Influence cascades are typically analyzed using a single metric approach, i.e., all influence is measured using one number. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific attributes. One such attribute could be whether the action is an initiation of a new post, a contribution to a post, or a sharing of an existing post. In this paper, we present a novel method for tracking these influence relationships over time, which we call influence cascades, and present a visualization technique to better understand these cascades. We investigate these influence patterns within and across online social media platforms using empirical data and comparing to a scale-free network as a null model. Our results show that characteristics of influence cascades and patterns of influence are, in fact, affected by the platform and the community of the users.
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.3390/e23020160
