The promise and the premise: How digital media present big data

Autores
Becerra, Gaston
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper analyzes the thematic and discursive construction of big data by the Argentine digital press. Using text mining techniques — topic modelling and enriched associative networks — together with qualitative and quantitative content analysis — in both discourse and images — over 2,026 articles, we sought to identify the topics wherein big data is treated, the promises and risks it addresses, its definition within the semantic field in which is explicitly expressed, and the pictures that illustrate it. Results herein presented compare how big data is portrayed in news about politics, business, and technological innovations, as well as in focal pieces targeted to a generic and massive audience, and critical reflections about its risks. Although in each of those thematic contexts big data is anchored differently, there is a common idea that associates big data with a socio-technological premise and an epistemic promise: because of the availability of large volumes of data, something new that will allow better decisions can be known. Our exploration contributes to a more detailed knowledge on how the news media social systems make sense of novel phenomena such as big data.
Fil: Becerra, Gaston. Universidad de Buenos Aires. Facultad de Filosofia y Letras. Instituto de Investigación en Ciencias de la Educación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
BIG DATA
CONSTRUCCIÓN MEDIÁTICA
MEDIOS DE MASAS
TEORIA DE SISTEMAS
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:11336/154252
Acceder
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network_name_str CONICET Digital (CONICET)
spelling The promise and the premise: How digital media present big dataBecerra, GastonBIG DATACONSTRUCCIÓN MEDIÁTICAMEDIOS DE MASASTEORIA DE SISTEMAShttps://purl.org/becyt/ford/5.4https://purl.org/becyt/ford/5This paper analyzes the thematic and discursive construction of big data by the Argentine digital press. Using text mining techniques — topic modelling and enriched associative networks — together with qualitative and quantitative content analysis — in both discourse and images — over 2,026 articles, we sought to identify the topics wherein big data is treated, the promises and risks it addresses, its definition within the semantic field in which is explicitly expressed, and the pictures that illustrate it. Results herein presented compare how big data is portrayed in news about politics, business, and technological innovations, as well as in focal pieces targeted to a generic and massive audience, and critical reflections about its risks. Although in each of those thematic contexts big data is anchored differently, there is a common idea that associates big data with a socio-technological premise and an epistemic promise: because of the availability of large volumes of data, something new that will allow better decisions can be known. Our exploration contributes to a more detailed knowledge on how the news media social systems make sense of novel phenomena such as big data.Fil: Becerra, Gaston. Universidad de Buenos Aires. Facultad de Filosofia y Letras. Instituto de Investigación en Ciencias de la Educación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaKøbenhavn2021-08-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/154252Becerra, Gaston; The promise and the premise: How digital media present big data; København; First Monday; 26; 9; 29-8-2021; 1-381396-04661396-0458CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://journals.uic.edu/ojs/index.php/fm/article/view/10539info:eu-repo/semantics/altIdentifier/doi/10.5210/fm.v26i9.10539info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:49:13Zoai:ri.conicet.gov.ar:11336/154252instacron: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:34982025-09-29 09:49:14.046CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv The promise and the premise: How digital media present big data
title The promise and the premise: How digital media present big data
spellingShingle The promise and the premise: How digital media present big data
Becerra, Gaston
BIG DATA
CONSTRUCCIÓN MEDIÁTICA
MEDIOS DE MASAS
TEORIA DE SISTEMAS
title_short The promise and the premise: How digital media present big data
title_full The promise and the premise: How digital media present big data
title_fullStr The promise and the premise: How digital media present big data
title_full_unstemmed The promise and the premise: How digital media present big data
title_sort The promise and the premise: How digital media present big data
dc.creator.none.fl_str_mv Becerra, Gaston
author Becerra, Gaston
author_facet Becerra, Gaston
author_role author
dc.subject.none.fl_str_mv BIG DATA
CONSTRUCCIÓN MEDIÁTICA
MEDIOS DE MASAS
TEORIA DE SISTEMAS
topic BIG DATA
CONSTRUCCIÓN MEDIÁTICA
MEDIOS DE MASAS
TEORIA DE SISTEMAS
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.4
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv This paper analyzes the thematic and discursive construction of big data by the Argentine digital press. Using text mining techniques — topic modelling and enriched associative networks — together with qualitative and quantitative content analysis — in both discourse and images — over 2,026 articles, we sought to identify the topics wherein big data is treated, the promises and risks it addresses, its definition within the semantic field in which is explicitly expressed, and the pictures that illustrate it. Results herein presented compare how big data is portrayed in news about politics, business, and technological innovations, as well as in focal pieces targeted to a generic and massive audience, and critical reflections about its risks. Although in each of those thematic contexts big data is anchored differently, there is a common idea that associates big data with a socio-technological premise and an epistemic promise: because of the availability of large volumes of data, something new that will allow better decisions can be known. Our exploration contributes to a more detailed knowledge on how the news media social systems make sense of novel phenomena such as big data.
Fil: Becerra, Gaston. Universidad de Buenos Aires. Facultad de Filosofia y Letras. Instituto de Investigación en Ciencias de la Educación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description This paper analyzes the thematic and discursive construction of big data by the Argentine digital press. Using text mining techniques — topic modelling and enriched associative networks — together with qualitative and quantitative content analysis — in both discourse and images — over 2,026 articles, we sought to identify the topics wherein big data is treated, the promises and risks it addresses, its definition within the semantic field in which is explicitly expressed, and the pictures that illustrate it. Results herein presented compare how big data is portrayed in news about politics, business, and technological innovations, as well as in focal pieces targeted to a generic and massive audience, and critical reflections about its risks. Although in each of those thematic contexts big data is anchored differently, there is a common idea that associates big data with a socio-technological premise and an epistemic promise: because of the availability of large volumes of data, something new that will allow better decisions can be known. Our exploration contributes to a more detailed knowledge on how the news media social systems make sense of novel phenomena such as big data.
publishDate 2021
dc.date.none.fl_str_mv 2021-08-29
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/11336/154252
Becerra, Gaston; The promise and the premise: How digital media present big data; København; First Monday; 26; 9; 29-8-2021; 1-38
1396-0466
1396-0458
CONICET Digital
CONICET
url http://hdl.handle.net/11336/154252
identifier_str_mv Becerra, Gaston; The promise and the premise: How digital media present big data; København; First Monday; 26; 9; 29-8-2021; 1-38
1396-0466
1396-0458
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://journals.uic.edu/ojs/index.php/fm/article/view/10539
info:eu-repo/semantics/altIdentifier/doi/10.5210/fm.v26i9.10539
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
dc.publisher.none.fl_str_mv København
publisher.none.fl_str_mv København
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
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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score 13.070432

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