Large-scale computational content analysis on magazines targeting men and women: the case of Argentina 2008-2018
Differences in magazines content aimed specifically at women or men are a means to create and reproduce gender stereotypes. Novel computational tools allow to study differences in magazines content taking into account all available articles. In this study, we analyse the case of two Argentinian maga...
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Published in | Feminist media studies Vol. 23; no. 5; pp. 2235 - 2253 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Abingdon
Routledge
04.07.2023
Taylor & Francis Ltd |
Subjects | |
Online Access | Get full text |
ISSN | 1468-0777 1471-5902 |
DOI | 10.1080/14680777.2022.2047090 |
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Abstract | Differences in magazines content aimed specifically at women or men are a means to create and reproduce gender stereotypes. Novel computational tools allow to study differences in magazines content taking into account all available articles. In this study, we analyse the case of two Argentinian magazines published by the same publishing house over a decade (2008-2018), advertised by the publishing house as targeting women and men respectively. Using computational tools, we are able to analyse more than 24,000 articles, which would have been an impossible task using manual content analysis methodologies. With Topic Modelling techniques we identify the main themes discussed in the magazines and quantify their different frequency between magazines over time. Then, we performed a word-frequency analysis to validate this methodology and extend the analysis to other subjects. Our results show that topics such as 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 are maintained. Also, we identify a considerable increase in the use of words associated with feminism since 2015 and specifically the word abortion in 2018. Furthermore, we develop a website where everyone can perform additional analysis. |
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AbstractList | Differences in magazines content aimed specifically at women or men are a means to create and reproduce gender stereotypes. Novel computational tools allow to study differences in magazines content taking into account all available articles. In this study, we analyse the case of two Argentinian magazines published by the same publishing house over a decade (2008-2018), advertised by the publishing house as targeting women and men respectively. Using computational tools, we are able to analyse more than 24,000 articles, which would have been an impossible task using manual content analysis methodologies. With Topic Modelling techniques we identify the main themes discussed in the magazines and quantify their different frequency between magazines over time. Then, we performed a word-frequency analysis to validate this methodology and extend the analysis to other subjects. Our results show that topics such as 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 are maintained. Also, we identify a considerable increase in the use of words associated with feminism since 2015 and specifically the word abortion in 2018. Furthermore, we develop a website where everyone can perform additional analysis. |
Author | Lozano, Gabriela Gonzalez, Fernando Altszyler, Edgar Felcher, Carla M. Kozlowski, Diego |
Author_xml | – sequence: 1 givenname: Diego orcidid: 0000-0002-5396-3471 surname: Kozlowski fullname: Kozlowski, Diego email: diego.kozlowski@uni.lu organization: University of Luxembourg – sequence: 2 givenname: Gabriela surname: Lozano fullname: Lozano, Gabriela organization: University of Buenos Aires – sequence: 3 givenname: Carla M. surname: Felcher fullname: Felcher, Carla M. organization: Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE), CONICET-Universidad de Buenos Aires – sequence: 4 givenname: Fernando surname: Gonzalez fullname: Gonzalez, Fernando organization: Universidad de Buenos Aires – sequence: 5 givenname: Edgar orcidid: 0000-0002-9397-8168 surname: Altszyler fullname: Altszyler, Edgar organization: Universidad de Buenos Aires. Instituto de Investigación en Ciencias de la Computación |
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SubjectTerms | Abortion computational social science Content analysis digital humanities Feminism Frequency analysis gender bias Gender differences Gender stereotypes Men natural language processing Publishing Software topic modelling Topics Women |
Title | Large-scale computational content analysis on magazines targeting men and women: the case of Argentina 2008-2018 |
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