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Proceedings Paper

Social relevance: toward understanding the impact of the individual in an information cascade
Author(s): Robert T. Hall; Joshua S. White; Jeremy Fields
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Paper Abstract

Information Cascades (IC) through a social network occur due to the decision of users to disseminate content. We define this decision process as User Diffusion (UD). IC models typically describe an information cascade by treating a user as a node within a social graph, where a node’s reception of an idea is represented by some activation state. The probability of activation then becomes a function of a node’s connectedness to other activated nodes as well as, potentially, the history of activation attempts. We enrich this Coarse-Grained User Diffusion (CGUD) model by applying actor type logics to the nodes of the graph. The resulting Fine-Grained User Diffusion (FGUD) model utilizes prior research in actor typing to generate a predictive model regarding the future influence a user will have on an Information Cascade. Furthermore, we introduce a measure of Information Resonance that is used to aid in predictions regarding user behavior.

Paper Details

Date Published: 12 May 2016
PDF: 9 pages
Proc. SPIE 9826, Cyber Sensing 2016, 98260C (12 May 2016); doi: 10.1117/12.2222888
Show Author Affiliations
Robert T. Hall, Rsignia Inc. (United States)
Joshua S. White, Rsignia Inc. (United States)
SUNY Polytechnic Institute (United States)
Jeremy Fields, SUNY Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 9826:
Cyber Sensing 2016
Igor V. Ternovskiy; Peter Chin, Editor(s)

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