Emergence of bursts and communities in evolving weighted networks.

Understanding the patterns of human dynamics and social interaction and the way they lead to the formation of an organized and functional society are important issues especially for techno-social development. Addressing these issues of social networks has recently become possible through large scale...

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Autores principales:	Hang-Hyun Jo, Raj Kumar Pan, Kimmo Kaski
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/de58d969885046a096fc0fc3442731d8
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spelling	oai:doaj.org-article:de58d969885046a096fc0fc3442731d82021-11-18T06:48:08ZEmergence of bursts and communities in evolving weighted networks.1932-620310.1371/journal.pone.0022687https://doaj.org/article/de58d969885046a096fc0fc3442731d82011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21857946/?tool=EBIhttps://doaj.org/toc/1932-6203Understanding the patterns of human dynamics and social interaction and the way they lead to the formation of an organized and functional society are important issues especially for techno-social development. Addressing these issues of social networks has recently become possible through large scale data analysis of mobile phone call records, which has revealed the existence of modular or community structure with many links between nodes of the same community and relatively few links between nodes of different communities. The weights of links, e.g., the number of calls between two users, and the network topology are found correlated such that intra-community links are stronger compared to the weak inter-community links. This feature is known as Granovetter's "The strength of weak ties" hypothesis. In addition to this inhomogeneous community structure, the temporal patterns of human dynamics turn out to be inhomogeneous or bursty, characterized by the heavy tailed distribution of time interval between two consecutive events, i.e., inter-event time. In this paper, we study how the community structure and the bursty dynamics emerge together in a simple evolving weighted network model. The principal mechanisms behind these patterns are social interaction by cyclic closure, i.e., links to friends of friends and the focal closure, links to individuals sharing similar attributes or interests, and human dynamics by task handling process. These three mechanisms have been implemented as a network model with local attachment, global attachment, and priority-based queuing processes. By comprehensive numerical simulations we show that the interplay of these mechanisms leads to the emergence of heavy tailed inter-event time distribution and the evolution of Granovetter-type community structure. Moreover, the numerical results are found to be in qualitative agreement with empirical analysis results from mobile phone call dataset.Hang-Hyun JoRaj Kumar PanKimmo KaskiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 8, p e22687 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Hang-Hyun Jo Raj Kumar Pan Kimmo Kaski Emergence of bursts and communities in evolving weighted networks.
description	Understanding the patterns of human dynamics and social interaction and the way they lead to the formation of an organized and functional society are important issues especially for techno-social development. Addressing these issues of social networks has recently become possible through large scale data analysis of mobile phone call records, which has revealed the existence of modular or community structure with many links between nodes of the same community and relatively few links between nodes of different communities. The weights of links, e.g., the number of calls between two users, and the network topology are found correlated such that intra-community links are stronger compared to the weak inter-community links. This feature is known as Granovetter's "The strength of weak ties" hypothesis. In addition to this inhomogeneous community structure, the temporal patterns of human dynamics turn out to be inhomogeneous or bursty, characterized by the heavy tailed distribution of time interval between two consecutive events, i.e., inter-event time. In this paper, we study how the community structure and the bursty dynamics emerge together in a simple evolving weighted network model. The principal mechanisms behind these patterns are social interaction by cyclic closure, i.e., links to friends of friends and the focal closure, links to individuals sharing similar attributes or interests, and human dynamics by task handling process. These three mechanisms have been implemented as a network model with local attachment, global attachment, and priority-based queuing processes. By comprehensive numerical simulations we show that the interplay of these mechanisms leads to the emergence of heavy tailed inter-event time distribution and the evolution of Granovetter-type community structure. Moreover, the numerical results are found to be in qualitative agreement with empirical analysis results from mobile phone call dataset.
format	article
author	Hang-Hyun Jo Raj Kumar Pan Kimmo Kaski
author_facet	Hang-Hyun Jo Raj Kumar Pan Kimmo Kaski
author_sort	Hang-Hyun Jo
title	Emergence of bursts and communities in evolving weighted networks.
title_short	Emergence of bursts and communities in evolving weighted networks.
title_full	Emergence of bursts and communities in evolving weighted networks.
title_fullStr	Emergence of bursts and communities in evolving weighted networks.
title_full_unstemmed	Emergence of bursts and communities in evolving weighted networks.
title_sort	emergence of bursts and communities in evolving weighted networks.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/de58d969885046a096fc0fc3442731d8
work_keys_str_mv	AT hanghyunjo emergenceofburstsandcommunitiesinevolvingweightednetworks AT rajkumarpan emergenceofburstsandcommunitiesinevolvingweightednetworks AT kimmokaski emergenceofburstsandcommunitiesinevolvingweightednetworks
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Emergence of bursts and communities in evolving weighted networks.

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