Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media

【Author】 Senevirathna, Chathurani; Gunaratne, Chathika; Rand, William; Jayalath, Chathura; Garibay, Ivan

【Source】ENTROPY

【影响因子】2.738

【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.

【Keywords】influence cascades; transfer entropy; online social networks; cross platforms; cryptocurrency; cyber-vulnerability

【发表时间】2021 FEB

【收录时间】2022-01-02

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