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Open source data reveals connection between online and on-street protest activity

There is enormous interest in inferring features of human behavior in the real world from potential digital footprints created online - particularly at the collective level, where the sheer volume of online activity may indicate some changing mood within the population regarding a particular topic....

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Detalles Bibliográficos
Autores principales: Qi, Hong, Manrique, Pedro, Johnson, Daniela, Restrepo, Elvira, Johnson, Neil F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944590/
https://www.ncbi.nlm.nih.gov/pubmed/27471660
http://dx.doi.org/10.1140/epjds/s13688-016-0081-5
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author Qi, Hong
Manrique, Pedro
Johnson, Daniela
Restrepo, Elvira
Johnson, Neil F
author_facet Qi, Hong
Manrique, Pedro
Johnson, Daniela
Restrepo, Elvira
Johnson, Neil F
author_sort Qi, Hong
collection PubMed
description There is enormous interest in inferring features of human behavior in the real world from potential digital footprints created online - particularly at the collective level, where the sheer volume of online activity may indicate some changing mood within the population regarding a particular topic. Civil unrest is a prime example, involving the spontaneous appearance of large crowds of otherwise unrelated people on the street on a certain day. While indicators of brewing protests might be gleaned from individual online communications or account content (e.g. Twitter, Facebook) societal concerns regarding privacy can make such probing a politically delicate issue. Here we show that instead, a simple low-level indicator of civil unrest can be obtained from online data at the aggregate level through Google Trends or similar tools. Our study covers countries across Latin America during 2011-2014 in which diverse civil unrest events took place. In each case, we find that the combination of the volume and momentum of searches from Google Trends surrounding pairs of simple keywords, tailored for the specific cultural setting, provide good indicators of periods of civil unrest. This proof-of-concept study motivates the search for more geographically specific indicators based on geo-located searches at the urban level.
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spelling pubmed-49445902016-07-26 Open source data reveals connection between online and on-street protest activity Qi, Hong Manrique, Pedro Johnson, Daniela Restrepo, Elvira Johnson, Neil F EPJ Data Sci Regular Article There is enormous interest in inferring features of human behavior in the real world from potential digital footprints created online - particularly at the collective level, where the sheer volume of online activity may indicate some changing mood within the population regarding a particular topic. Civil unrest is a prime example, involving the spontaneous appearance of large crowds of otherwise unrelated people on the street on a certain day. While indicators of brewing protests might be gleaned from individual online communications or account content (e.g. Twitter, Facebook) societal concerns regarding privacy can make such probing a politically delicate issue. Here we show that instead, a simple low-level indicator of civil unrest can be obtained from online data at the aggregate level through Google Trends or similar tools. Our study covers countries across Latin America during 2011-2014 in which diverse civil unrest events took place. In each case, we find that the combination of the volume and momentum of searches from Google Trends surrounding pairs of simple keywords, tailored for the specific cultural setting, provide good indicators of periods of civil unrest. This proof-of-concept study motivates the search for more geographically specific indicators based on geo-located searches at the urban level. Springer Berlin Heidelberg 2016-05-06 2016 /pmc/articles/PMC4944590/ /pubmed/27471660 http://dx.doi.org/10.1140/epjds/s13688-016-0081-5 Text en © Qi et al. 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Regular Article
Qi, Hong
Manrique, Pedro
Johnson, Daniela
Restrepo, Elvira
Johnson, Neil F
Open source data reveals connection between online and on-street protest activity
title Open source data reveals connection between online and on-street protest activity
title_full Open source data reveals connection between online and on-street protest activity
title_fullStr Open source data reveals connection between online and on-street protest activity
title_full_unstemmed Open source data reveals connection between online and on-street protest activity
title_short Open source data reveals connection between online and on-street protest activity
title_sort open source data reveals connection between online and on-street protest activity
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944590/
https://www.ncbi.nlm.nih.gov/pubmed/27471660
http://dx.doi.org/10.1140/epjds/s13688-016-0081-5
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