Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/115310
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Type: Conference paper
Title: The nature and origin of heavy tails in retweet activity
Author: Mathews, P.
Mitchell, L.
Nguyen, G.T.
Bean, N.G.
Citation: Proceedings of the 26th International World Wide Web Conference, 2017, pp.1493-1498
Publisher: Association for Computing Machinery
Issue Date: 2017
ISBN: 9781450349147
Conference Name: 26th International World Wide Web Conference (WWW 2017) (3 Apr 2017 - 7 Apr 2017 : Perth, Australia)
Statement of
Responsibility: 
Peter Mathews, Lewis Mitchell, Giang Nguyen, Nigel Bean
Abstract: Modern social media platforms facilitate the rapid spread of information online. Modelling phenomena such as social contagion and information diffusion are contingent upon a detailed understanding of the information-sharing processes. In Twitter, an important aspect of this occurs with retweets, where users rebroadcast the tweets of other users. To improve our understanding of how these distributions arise, we analyse the distribution of retweet times. We show that a power law with exponential cutoff provides a better fit than the power laws previously suggested. We explain this fit through the burstiness of human behaviour and the priorities individuals place on different tasks.
Keywords: Retweet; Twitter; power law; power law with exponential cutoff
Description: WWW 2017 Companion
Rights: © 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License.
DOI: 10.1145/3041021.3053903
Published version: http://dx.doi.org/10.1145/3041021.3053903
Appears in Collections:Aurora harvest 3
Mathematical Sciences publications

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