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How Do Online Social Networks Grow?
Online social networks such as Facebook, Twitter and Gowalla allow people to communicate and interact across borders. In past years online social networks have become increasingly important for studying the behavior of individuals, group formation, and the emergence of online societies. Here we focu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4062482/ https://www.ncbi.nlm.nih.gov/pubmed/24940744 http://dx.doi.org/10.1371/journal.pone.0100023 |
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author | Zhu, Konglin Li, Wenzhong Fu, Xiaoming Nagler, Jan |
author_facet | Zhu, Konglin Li, Wenzhong Fu, Xiaoming Nagler, Jan |
author_sort | Zhu, Konglin |
collection | PubMed |
description | Online social networks such as Facebook, Twitter and Gowalla allow people to communicate and interact across borders. In past years online social networks have become increasingly important for studying the behavior of individuals, group formation, and the emergence of online societies. Here we focus on the characterization of the average growth of online social networks and try to understand which are possible processes behind seemingly long-range temporal correlated collective behavior. In agreement with recent findings, but in contrast to Gibrat's law of proportionate growth, we find scaling in the average growth rate and its standard deviation. In contrast, Renren and Twitter deviate, however, in certain important aspects significantly from those found in many social and economic systems. Whereas independent methods suggest no significance for temporally long-range correlated behavior for Renren and Twitter, a scaling analysis of the standard deviation does suggest long-range temporal correlated growth in Gowalla. However, we demonstrate that seemingly long-range temporal correlations in the growth of online social networks, such as in Gowalla, can be explained by a decomposition into temporally and spatially independent growth processes with a large variety of entry rates. Our analysis thus suggests that temporally or spatially correlated behavior does not play a major role in the growth of online social networks. |
format | Online Article Text |
id | pubmed-4062482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40624822014-06-24 How Do Online Social Networks Grow? Zhu, Konglin Li, Wenzhong Fu, Xiaoming Nagler, Jan PLoS One Research Article Online social networks such as Facebook, Twitter and Gowalla allow people to communicate and interact across borders. In past years online social networks have become increasingly important for studying the behavior of individuals, group formation, and the emergence of online societies. Here we focus on the characterization of the average growth of online social networks and try to understand which are possible processes behind seemingly long-range temporal correlated collective behavior. In agreement with recent findings, but in contrast to Gibrat's law of proportionate growth, we find scaling in the average growth rate and its standard deviation. In contrast, Renren and Twitter deviate, however, in certain important aspects significantly from those found in many social and economic systems. Whereas independent methods suggest no significance for temporally long-range correlated behavior for Renren and Twitter, a scaling analysis of the standard deviation does suggest long-range temporal correlated growth in Gowalla. However, we demonstrate that seemingly long-range temporal correlations in the growth of online social networks, such as in Gowalla, can be explained by a decomposition into temporally and spatially independent growth processes with a large variety of entry rates. Our analysis thus suggests that temporally or spatially correlated behavior does not play a major role in the growth of online social networks. Public Library of Science 2014-06-18 /pmc/articles/PMC4062482/ /pubmed/24940744 http://dx.doi.org/10.1371/journal.pone.0100023 Text en © 2014 Zhu 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Zhu, Konglin Li, Wenzhong Fu, Xiaoming Nagler, Jan How Do Online Social Networks Grow? |
title | How Do Online Social Networks Grow? |
title_full | How Do Online Social Networks Grow? |
title_fullStr | How Do Online Social Networks Grow? |
title_full_unstemmed | How Do Online Social Networks Grow? |
title_short | How Do Online Social Networks Grow? |
title_sort | how do online social networks grow? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4062482/ https://www.ncbi.nlm.nih.gov/pubmed/24940744 http://dx.doi.org/10.1371/journal.pone.0100023 |
work_keys_str_mv | AT zhukonglin howdoonlinesocialnetworksgrow AT liwenzhong howdoonlinesocialnetworksgrow AT fuxiaoming howdoonlinesocialnetworksgrow AT naglerjan howdoonlinesocialnetworksgrow |