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Stationarity of the inter-event power-law distributions

A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of these processes generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon...

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Detalles Bibliográficos
Autores principales: Gandica, Yerali, Carvalho, João, Sampaio dos Aidos, Fernando, Lambiotte, Renaud, Carletti, Timoteo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367707/
https://www.ncbi.nlm.nih.gov/pubmed/28346480
http://dx.doi.org/10.1371/journal.pone.0174509
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author Gandica, Yerali
Carvalho, João
Sampaio dos Aidos, Fernando
Lambiotte, Renaud
Carletti, Timoteo
author_facet Gandica, Yerali
Carvalho, João
Sampaio dos Aidos, Fernando
Lambiotte, Renaud
Carletti, Timoteo
author_sort Gandica, Yerali
collection PubMed
description A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of these processes generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon are not yet clearly understood. In the present work we use the freely available Wikipedia’s editing records to unravel some features of this phenomenon. We show that even though the probability to start editing is conditioned by the circadian 24 hour cycle, the conditional probability for the time interval between successive edits at a given time of the day is independent from the latter. We confirm our findings with the activity of posting on the social network Twitter. Our results suggest that there is an intrinsic humankind scheduling pattern: after overcoming the encumbrance of starting an activity, there is a robust distribution of new related actions, which does not depend on the time of day at which the activity started.
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spelling pubmed-53677072017-04-06 Stationarity of the inter-event power-law distributions Gandica, Yerali Carvalho, João Sampaio dos Aidos, Fernando Lambiotte, Renaud Carletti, Timoteo PLoS One Research Article A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of these processes generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon are not yet clearly understood. In the present work we use the freely available Wikipedia’s editing records to unravel some features of this phenomenon. We show that even though the probability to start editing is conditioned by the circadian 24 hour cycle, the conditional probability for the time interval between successive edits at a given time of the day is independent from the latter. We confirm our findings with the activity of posting on the social network Twitter. Our results suggest that there is an intrinsic humankind scheduling pattern: after overcoming the encumbrance of starting an activity, there is a robust distribution of new related actions, which does not depend on the time of day at which the activity started. Public Library of Science 2017-03-27 /pmc/articles/PMC5367707/ /pubmed/28346480 http://dx.doi.org/10.1371/journal.pone.0174509 Text en © 2017 Gandica et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gandica, Yerali
Carvalho, João
Sampaio dos Aidos, Fernando
Lambiotte, Renaud
Carletti, Timoteo
Stationarity of the inter-event power-law distributions
title Stationarity of the inter-event power-law distributions
title_full Stationarity of the inter-event power-law distributions
title_fullStr Stationarity of the inter-event power-law distributions
title_full_unstemmed Stationarity of the inter-event power-law distributions
title_short Stationarity of the inter-event power-law distributions
title_sort stationarity of the inter-event power-law distributions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367707/
https://www.ncbi.nlm.nih.gov/pubmed/28346480
http://dx.doi.org/10.1371/journal.pone.0174509
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