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How Random are Online Social Interactions?
The massive amounts of data that social media generates has facilitated the study of online human behavior on a scale unimaginable a few years ago. At the same time, the much discussed apparent randomness with which people interact online makes it appear as if these studies cannot reveal predictive...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3433691/ https://www.ncbi.nlm.nih.gov/pubmed/22953054 http://dx.doi.org/10.1038/srep00633 |
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author | Wang, Chunyan Huberman, Bernardo A. |
author_facet | Wang, Chunyan Huberman, Bernardo A. |
author_sort | Wang, Chunyan |
collection | PubMed |
description | The massive amounts of data that social media generates has facilitated the study of online human behavior on a scale unimaginable a few years ago. At the same time, the much discussed apparent randomness with which people interact online makes it appear as if these studies cannot reveal predictive social behaviors that could be used for developing better platforms and services. We use two large social databases to measure the mutual information entropy that both individual and group actions generate as they evolve over time. We show that user's interaction sequences have strong deterministic components, in contrast with existing assumptions and models. In addition, we show that individual interactions are more predictable when users act on their own rather than when attending group activities. |
format | Online Article Text |
id | pubmed-3433691 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-34336912012-09-05 How Random are Online Social Interactions? Wang, Chunyan Huberman, Bernardo A. Sci Rep Article The massive amounts of data that social media generates has facilitated the study of online human behavior on a scale unimaginable a few years ago. At the same time, the much discussed apparent randomness with which people interact online makes it appear as if these studies cannot reveal predictive social behaviors that could be used for developing better platforms and services. We use two large social databases to measure the mutual information entropy that both individual and group actions generate as they evolve over time. We show that user's interaction sequences have strong deterministic components, in contrast with existing assumptions and models. In addition, we show that individual interactions are more predictable when users act on their own rather than when attending group activities. Nature Publishing Group 2012-09-05 /pmc/articles/PMC3433691/ /pubmed/22953054 http://dx.doi.org/10.1038/srep00633 Text en Copyright © 2012, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Article Wang, Chunyan Huberman, Bernardo A. How Random are Online Social Interactions? |
title | How Random are Online Social Interactions? |
title_full | How Random are Online Social Interactions? |
title_fullStr | How Random are Online Social Interactions? |
title_full_unstemmed | How Random are Online Social Interactions? |
title_short | How Random are Online Social Interactions? |
title_sort | how random are online social interactions? |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3433691/ https://www.ncbi.nlm.nih.gov/pubmed/22953054 http://dx.doi.org/10.1038/srep00633 |
work_keys_str_mv | AT wangchunyan howrandomareonlinesocialinteractions AT hubermanbernardoa howrandomareonlinesocialinteractions |