Point process analysis of geographical diffusion of news in Argentina

Autores
Garcia, Lucio Lorenzo; Tirabassi, Giulio; Masoller, Cristina; Balenzuela, Pablo
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The diffusion of information plays a crucial role in a society, affecting its economy and the well-being of the population. Characterizing the diffusion process is challenging because it is highly non-stationary and varies with the media type. To understand the spreading of newspapernews in Argentina, we collected data from more than 27 000 articles published in six main provinces during 4 months. We classified the articles into 20 thematic axes and obtained a set of time series that capture daily newspaper attention on different topics in different provinces. Toanalyze the data, we use a point process approach. For each topic, n, and for all pairs of provinces, i and j, we use two measures to quantify the synchronicity of the events, Qs (i, j), which quantifies the number of events that occur almost simultaneously in i and j, and Qa (i, j), which quantifies the direction of news spreading. Our analysis unveils how fast the information diffusion process is, showing pairs of provinces with very similar and almost simultaneous temporal variations of media attention. On the other hand, we also calculate other measures computed from the raw time series, such as Granger Causality and Transfer Entropy, which do not perform well in this context because they often return opposite directions of information transfer. We interpret this as due to the characteristics of the data, which is highly non-stationary, and of the information diffusion process, which is very fast and probably acts at a sub-resolution time scale.
Fil: Garcia, Lucio Lorenzo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Tirabassi, Giulio. Universidad Politécnica de Catalunya. Departament de Física Enginyeria; España. Universidad de Girona; España
Fil: Masoller, Cristina. Universidad Politécnica de Catalunya. Departament de Física Enginyeria; España
Fil: Balenzuela, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Materia
Information difussion
Point process
Causality measures
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/274574
Acceder
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spelling Point process analysis of geographical diffusion of news in ArgentinaGarcia, Lucio LorenzoTirabassi, GiulioMasoller, CristinaBalenzuela, PabloInformation difussionPoint processCausality measureshttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1The diffusion of information plays a crucial role in a society, affecting its economy and the well-being of the population. Characterizing the diffusion process is challenging because it is highly non-stationary and varies with the media type. To understand the spreading of newspapernews in Argentina, we collected data from more than 27 000 articles published in six main provinces during 4 months. We classified the articles into 20 thematic axes and obtained a set of time series that capture daily newspaper attention on different topics in different provinces. Toanalyze the data, we use a point process approach. For each topic, n, and for all pairs of provinces, i and j, we use two measures to quantify the synchronicity of the events, Qs (i, j), which quantifies the number of events that occur almost simultaneously in i and j, and Qa (i, j), which quantifies the direction of news spreading. Our analysis unveils how fast the information diffusion process is, showing pairs of provinces with very similar and almost simultaneous temporal variations of media attention. On the other hand, we also calculate other measures computed from the raw time series, such as Granger Causality and Transfer Entropy, which do not perform well in this context because they often return opposite directions of information transfer. We interpret this as due to the characteristics of the data, which is highly non-stationary, and of the information diffusion process, which is very fast and probably acts at a sub-resolution time scale.Fil: Garcia, Lucio Lorenzo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Tirabassi, Giulio. Universidad Politécnica de Catalunya. Departament de Física Enginyeria; España. Universidad de Girona; EspañaFil: Masoller, Cristina. Universidad Politécnica de Catalunya. Departament de Física Enginyeria; EspañaFil: Balenzuela, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaAmerican Institute of Physics2025-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/274574Garcia, Lucio Lorenzo; Tirabassi, Giulio; Masoller, Cristina; Balenzuela, Pablo; Point process analysis of geographical diffusion of news in Argentina; American Institute of Physics; Chaos; 35; 1; 1-2025; 1-351054-1500CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://pubs.aip.org/aip/cha/article-abstract/35/1/013135/3331491/Point-process-analysis-of-geographical-diffusioninfo:eu-repo/semantics/altIdentifier/doi/10.1063/5.0240799info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-05T10:24:58Zoai:ri.conicet.gov.ar:11336/274574instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-05 10:24:59.169CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Point process analysis of geographical diffusion of news in Argentina
title Point process analysis of geographical diffusion of news in Argentina
spellingShingle Point process analysis of geographical diffusion of news in Argentina
Garcia, Lucio Lorenzo
Information difussion
Point process
Causality measures
title_short Point process analysis of geographical diffusion of news in Argentina
title_full Point process analysis of geographical diffusion of news in Argentina
title_fullStr Point process analysis of geographical diffusion of news in Argentina
title_full_unstemmed Point process analysis of geographical diffusion of news in Argentina
title_sort Point process analysis of geographical diffusion of news in Argentina
dc.creator.none.fl_str_mv Garcia, Lucio Lorenzo
Tirabassi, Giulio
Masoller, Cristina
Balenzuela, Pablo
author Garcia, Lucio Lorenzo
author_facet Garcia, Lucio Lorenzo
Tirabassi, Giulio
Masoller, Cristina
Balenzuela, Pablo
author_role author
author2 Tirabassi, Giulio
Masoller, Cristina
Balenzuela, Pablo
author2_role author
author
author
dc.subject.none.fl_str_mv Information difussion
Point process
Causality measures
topic Information difussion
Point process
Causality measures
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The diffusion of information plays a crucial role in a society, affecting its economy and the well-being of the population. Characterizing the diffusion process is challenging because it is highly non-stationary and varies with the media type. To understand the spreading of newspapernews in Argentina, we collected data from more than 27 000 articles published in six main provinces during 4 months. We classified the articles into 20 thematic axes and obtained a set of time series that capture daily newspaper attention on different topics in different provinces. Toanalyze the data, we use a point process approach. For each topic, n, and for all pairs of provinces, i and j, we use two measures to quantify the synchronicity of the events, Qs (i, j), which quantifies the number of events that occur almost simultaneously in i and j, and Qa (i, j), which quantifies the direction of news spreading. Our analysis unveils how fast the information diffusion process is, showing pairs of provinces with very similar and almost simultaneous temporal variations of media attention. On the other hand, we also calculate other measures computed from the raw time series, such as Granger Causality and Transfer Entropy, which do not perform well in this context because they often return opposite directions of information transfer. We interpret this as due to the characteristics of the data, which is highly non-stationary, and of the information diffusion process, which is very fast and probably acts at a sub-resolution time scale.
Fil: Garcia, Lucio Lorenzo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Tirabassi, Giulio. Universidad Politécnica de Catalunya. Departament de Física Enginyeria; España. Universidad de Girona; España
Fil: Masoller, Cristina. Universidad Politécnica de Catalunya. Departament de Física Enginyeria; España
Fil: Balenzuela, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
description The diffusion of information plays a crucial role in a society, affecting its economy and the well-being of the population. Characterizing the diffusion process is challenging because it is highly non-stationary and varies with the media type. To understand the spreading of newspapernews in Argentina, we collected data from more than 27 000 articles published in six main provinces during 4 months. We classified the articles into 20 thematic axes and obtained a set of time series that capture daily newspaper attention on different topics in different provinces. Toanalyze the data, we use a point process approach. For each topic, n, and for all pairs of provinces, i and j, we use two measures to quantify the synchronicity of the events, Qs (i, j), which quantifies the number of events that occur almost simultaneously in i and j, and Qa (i, j), which quantifies the direction of news spreading. Our analysis unveils how fast the information diffusion process is, showing pairs of provinces with very similar and almost simultaneous temporal variations of media attention. On the other hand, we also calculate other measures computed from the raw time series, such as Granger Causality and Transfer Entropy, which do not perform well in this context because they often return opposite directions of information transfer. We interpret this as due to the characteristics of the data, which is highly non-stationary, and of the information diffusion process, which is very fast and probably acts at a sub-resolution time scale.
publishDate 2025
dc.date.none.fl_str_mv 2025-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/274574
Garcia, Lucio Lorenzo; Tirabassi, Giulio; Masoller, Cristina; Balenzuela, Pablo; Point process analysis of geographical diffusion of news in Argentina; American Institute of Physics; Chaos; 35; 1; 1-2025; 1-35
1054-1500
CONICET Digital
CONICET
url http://hdl.handle.net/11336/274574
identifier_str_mv Garcia, Lucio Lorenzo; Tirabassi, Giulio; Masoller, Cristina; Balenzuela, Pablo; Point process analysis of geographical diffusion of news in Argentina; American Institute of Physics; Chaos; 35; 1; 1-2025; 1-35
1054-1500
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://pubs.aip.org/aip/cha/article-abstract/35/1/013135/3331491/Point-process-analysis-of-geographical-diffusion
info:eu-repo/semantics/altIdentifier/doi/10.1063/5.0240799
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
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dc.publisher.none.fl_str_mv American Institute of Physics
publisher.none.fl_str_mv American Institute of Physics
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reponame_str CONICET Digital (CONICET)
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instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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