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dc.contributor.authorMorales i Gras, Jordi
dc.contributor.authorOrbegozo Terradillos, Julen
dc.contributor.authorLarrondo Ureta, Ainara
dc.contributor.authorPeña Fernández, Simón ORCID
dc.date.accessioned2021-11-25T15:39:20Z
dc.date.available2021-11-25T15:39:20Z
dc.date.issued2021-11-24
dc.identifier.citationBig Data and Cognitive Computing 5(4) : 2021 // Article ID 69es_ES
dc.identifier.issn2504-2289
dc.identifier.urihttp://hdl.handle.net/10810/54083
dc.descriptionThis article belongs to the Special Issue of Big Data Cogn.Comput.= "Big Data Analytics for Cultural Heritage"es_ES
dc.description.abstractInternet social media is a key space in which the memorial resources of social movements, including the stories and knowledge of previous generations, are organised, disseminated, and reinterpreted. This is especially important for movements such as feminism, which places great emphasis on the transmission of an intangible cultural legacy between its different generations or waves, which are conformed through these cultural transmissions. In this sense, several authors have highlighted the importance of social media and hashtivism in shaping the fourth wave of feminism that has been taking place in recent years (e.g., #metoo). The aim of this article is to present to the scientific community a hybrid methodological proposal for the network and content analysis of audiences and their interactions on Twitter: we will do so by describing and evaluating the results of different research we have carried out in the field of feminist hashtivism. Structural analysis methods such as social network analysis have demonstrated their capacity to be applied to the analysis of social media interactions as a mixed methodology, that is, both quantitative and qualitative. This article shows the potential of a specific methodological process that combines inductive and inferential reasoning with hypothetico-deductive approaches. By applying the methodology developed in the case studies included in the article, it is shown that these two modes of reasoning work best when they are used together.es_ES
dc.description.sponsorshipThis research was funded by Basque Government grant number IT-1112.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es
dc.subjectsocial movementses_ES
dc.subjectgender studieses_ES
dc.subjectsocial networkses_ES
dc.subjectsocial network analysises_ES
dc.subjectsocial mediaes_ES
dc.subjectfeminismes_ES
dc.subjecthashtivismes_ES
dc.subjectTwitteres_ES
dc.subjectMachine Learninges_ES
dc.titleNetworks and Stories. Analyzing the Transmission of the Feminist Intangible Cultural Heritage on Twitteres_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/2504-2289/5/4/69es_ES
dc.identifier.doi10.3390/bdcc5040069
dc.departamentoesPeriodismo IIes_ES
dc.departamentoeuKazetaritza IIes_ES


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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).