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Type: Conference paper
Title: Super-blockers and the effect of network structure on information cascades
Author: Gray, C.G.
Mitchell, L.
Roughan, M.
Citation: Proceedings of the 1st International Workshop on Online Social Networks and Media: Network Properties and D ynamics (OSNED 2018), as published in WWW ’18 Companion: The 2018 Web Conference Companion, 2018, pp.1435-1441
Publisher: Association for Computing Machinery
Publisher Place: New York
Issue Date: 2018
ISBN: 9781450356404
Conference Name: 1st International Workshop on Online Social Networks and Media: Network Properties and Dynamics (OSNED) (23 Apr 2018 - 27 Apr 2018 : Lyon, France)
Statement of
Caitlin Gray, Lewis Mitchell, Matthew Roughan
Abstract: Modelling information cascades over online social networks is important in fields from marketing to civil unrest prediction, however the underlying network structure strongly affects the probability and nature of such cascades. Even with simple cascade dynamics the probability of large cascades are almost entirely dictated by network properties, with well-known networks such as Erdos-Renyi and Barabasi-Albert producing wildly different cascades from the same model. Indeed, the notion of ‘superspreaders’ has arisen to describe highly influential nodes promoting global cascades in a social network. Here we use a simple model of global cascades to show that the presence of locality in the network increases the probability of a global cascade due to the increased vulnerability of connecting nodes. Rather than ‘super-spreaders’, we find that the presence of these highly connected ‘super-blockers’ in heavy-tailed networks in fact reduces the probability of global cascades, while promoting information spread when targeted as the initial spreader.
Keywords: Network Structure; Information diffusion; Cascades
Description: Part of 27th International World Wide Web Conference.
Rights: © 2018 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC BY 4.0 License. This paper is published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Authors reserve their rights to disseminate the work on their personal and corporate Web sites with the appropriate attribution.
DOI: 10.1145/3184558.3191590
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Mathematical Sciences publications

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