Application of statistics to framing and text mining in communication studies
Techniques of discourse analysis in the media have undergone a great evolution thanks to the ‘framing’ theory, but over time it has been perceived that the researchers’ studies could include high levels of subjectivity. To solve this problem, more objective methodologies have been developed, adaptin...
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| Autores principales: | , |
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| Formato: | Artículo publishedVersion |
| Lenguaje: | Español |
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Universidad de Buenos Aires, Facultad de Filosofía y Letras
2018
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| Acceso en línea: | https://revistascientificas.filo.uba.ar/index.php/ICS/article/view/4260 https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=biblioinfo&d=4260_oai |
| Aporte de: |
| Sumario: | Techniques of discourse analysis in the media have undergone a great evolution thanks to the ‘framing’ theory, but over time it has been perceived that the researchers’ studies could include high levels of subjectivity. To solve this problem, more objective methodologies have been developed, adapting statistical techniques to the examination of the main frames; cluster analysis being one of the most significant elements within these processes. More recent methods, such as text mining, propose the analysis to be entirely done through computer algorithms with morphological knowledge of different languages. This article approaches the state of the art of these methodologies, their most outstanding tools and the computer softwares that help in the statistical analysis of framing, with the aim of systematizing the options that are currently available for communication research. |
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