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dc.contributor.author
Diego Kozlowski  
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Lozano Rubello, Gabriela  
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Felcher, Carla María  
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Gonzalez, Fernando  
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Altszyler Lemcovich, Edgar Jaim  
dc.date.available
2021-10-02T01:16:22Z  
dc.date.issued
2020-11  
dc.identifier.citation
Diego Kozlowski; Lozano Rubello, Gabriela; Felcher, Carla María; Gonzalez, Fernando; Altszyler Lemcovich, Edgar Jaim; Gender bias in magazines oriented to men and women: a computational approach; ArXiv; ArXiv; 2020; 11-2020; 1-29  
dc.identifier.uri
http://hdl.handle.net/11336/142331  
dc.description.abstract
Cultural products are a source to acquire individual values and behaviours. Therefore, the differences in the content of the magazines aimed specifically at women or men are a means to create and reproduce gender stereotypes. In this study, we compare the content of a women-oriented magazine with that of a men-oriented one, both produced by the same editorial group, over a decade (2008-2018). With Topic Modelling techniques we identify the main themes discussed in the magazines and quantify how much the presence of these topics differs between magazines over time. Then, we performed a word-frequency analysis to validate this methodology andextend the analysis to other subjects that did not emerge automatically. Our results show that the frequency of appearance of the topics Family, Business and Women as sex objects, present an initial bias that tends to disappear over time. Conversely, in Fashion and Science topics, the initial differences between both magazines are maintained. Besides, we show that in 2012, the content associated with horoscope increased in the women-oriented magazine, generating a new gap that remained open over time. Also, we show a strong increase in the use of words associated with feminism since 2015 and specifically the word abortion in 2018. Overall, these computational tools allowed us to analyse more than 24,000 articles. Up to our knowledge, this is the first study to compare magazines in such a large dataset, a task that would have been prohibitive using manual content analysis methodologies.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
ArXiv  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Magazines  
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Natural Language Processing  
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Digital Humanities  
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Gender bias  
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Computational Social Science  
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Topic Modelling  
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Tópicos Sociales  
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Sociología  
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CIENCIAS SOCIALES  
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Comunicación de Medios y Socio-cultural  
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Comunicación y Medios  
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CIENCIAS SOCIALES  
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Ciencias de la Información y Bioinformática  
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Ciencias de la Computación e Información  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Gender bias in magazines oriented to men and women: a computational approach  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2021-04-28T21:04:19Z  
dc.identifier.eissn
2331-8422  
dc.journal.volume
2020  
dc.journal.pagination
1-29  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Diego Kozlowski. University of Luxembourg; Luxemburgo  
dc.description.fil
Fil: Lozano Rubello, Gabriela. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto Interdisciplinario de Estudios de Género; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Felcher, Carla María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina  
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Fil: Gonzalez, Fernando. Universidad de Buenos Aires; Argentina  
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Fil: Altszyler Lemcovich, Edgar Jaim. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina  
dc.journal.title
ArXiv  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/pdf/2011.12096.pdf