The Use of Supervised Learning Algorithms in Political Communication and Media Studies: Locating Frames in the Press
To 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 ca...
| Authors: | , |
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| Format: | article |
| Publication Date: | 2018 |
| Country: | España |
| Institution: | Universidad Complutense de Madrid (UCM) |
| Repository: | Docta Complutense |
| Language: | English |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/12796 |
| Online Access: | https://hdl.handle.net/20.500.14352/12796 |
| Access Level: | Open access |
| Keyword: | Algorithms Framing Press Spain SVM Refugees Refugee crisis Informática (Informática) Inteligencia artificial (Informática) Política Ciencias de la Información Periodismo 1203.17 Informática 1203.04 Inteligencia Artificial 59 Ciencia Política 5910.01 Información 5506.11 Historia del Periodismo |
| Summary: | To 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. |
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