The Use of Supervised Learning Algorithms in Political Communication and Media Studies: Locating Frames in the Press

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dc.contributor.authorCalatrava García, Adolfo
dc.contributor.authorGarcía-Marín, Javier
dc.date.accessioned2023-06-17T12:41:49Z
dc.date.available2023-06-17T12:41:49Z
dc.date.issued2018
dc.description.abstractTo locate media frames is one of the biggest challenges facing academics in Political Communication disciplines. The traditional approach to the problem is the use of different coders and their subsequent comparison, either through statistical analysis, or through agreements between them. In both cases, problems arise due to the difficulty of defining exactly where the frame is as well as its meaning and implications. And, above all, it is a complex process that makes it very difficult to work with large data sets. The authors, however, propose the use of information cataloging algorithms as a way to solve these problems. These algorithms (Support Vector Machines, Random Forest, CNN, etc.) come from disciplines linked to neural networks and have become an industry standard devoted to the treatment of non-numerical information and natural language processing. In addition, when supervised, they can be trained to find the information that the researcher considers pertinent. The authors present one case study, the media framing of the refugee crisis in Europe (in 2015) as an example. In that regard, SVM shows a lot of potential, being able to locate frames successfully albeit with some limitations.
dc.description.departmentDepto. de Relaciones Internacionales e Historia Global
dc.description.facultyFac. de Ciencias Políticas y Sociología
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/70997
dc.identifier.issn2174-0895
dc.identifier.officialurlhttps://revistas.unav.edu/index.php/communication-and-society/article/view/35695
dc.identifier.urihttps://hdl.handle.net/20.500.14352/12796
dc.issue.number3
dc.journal.titleCommunication & Society
dc.language.isoeng
dc.page.final188
dc.page.initial175
dc.publisherUniversidad de Navarra
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.keywordAlgorithms
dc.subject.keywordFraming
dc.subject.keywordPress
dc.subject.keywordSpain
dc.subject.keywordSVM
dc.subject.keywordRefugees
dc.subject.keywordRefugee crisis
dc.subject.ucmInformática (Informática)
dc.subject.ucmInteligencia artificial (Informática)
dc.subject.ucmPolítica
dc.subject.ucmCiencias de la Información
dc.subject.ucmPeriodismo
dc.subject.unesco1203.17 Informática
dc.subject.unesco1203.04 Inteligencia Artificial
dc.subject.unesco59 Ciencia Política
dc.subject.unesco5910.01 Información
dc.subject.unesco5506.11 Historia del Periodismo
dc.titleThe Use of Supervised Learning Algorithms in Political Communication and Media Studies: Locating Frames in the Press
dc.typejournal article
dc.volume.number31
dspace.entity.typePublication
relation.isAuthorOfPublication1558d1c8-83b7-4638-9d30-66ce7475dcf3
relation.isAuthorOfPublication.latestForDiscovery1558d1c8-83b7-4638-9d30-66ce7475dcf3
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