Analysis of Wikipedia Coverage in Spanish-Language Media between 2013 to 2023
Descripción del Articulo
This article analyses Wikipedia’s coverage in news from Spanish-speaking digital media. Framing Theory is used to examine how media outlets present Wikipedia in their article headlines. A total of 652 news articles were analyzed from the Factiva database between the years 2013 and 2023. Various anal...
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| Formato: | artículo |
| Fecha de Publicación: | 2025 |
| Institución: | Universidad de Piura |
| Repositorio: | Revista de Comunicación |
| Lenguaje: | español |
| OAI Identifier: | oai:revistas.udep.edu.pe:article/3726 |
| Enlace del recurso: | https://revistadecomunicacion.com/article/view/3726 |
| Nivel de acceso: | acceso abierto |
| Materia: | Enciclopedias Prensa y Lengua Española Cobertura informática Teoría de la comunicación Análsis de datos Análisis de tendencias Análisis de contenido Comunidades virtuales Igualdad de género Análisis léxico Encyclopaedias Press and Spanish Language News Coverage Communication Theory Data Analysis Trend Analysis Content Analysis Virtual Communities Gender Equality Lexical Analysis |
| Sumario: | This article analyses Wikipedia’s coverage in news from Spanish-speaking digital media. Framing Theory is used to examine how media outlets present Wikipedia in their article headlines. A total of 652 news articles were analyzed from the Factiva database between the years 2013 and 2023. Various analyses were conducted, including the distribution and temporal trends of the news, word frequency and heatmaps, the Latent Dirichlet Allocation (LDA) algorithm, and word co-occurrence in content and headlines. Natural language processing and machine learning techniques were applied for topic analysis. The results show that Spanish media has published the most about Wikipedia, with increased coverage during global events such as the COVID-19 pandemic and the Ukraine conflict. Controversies related to the biographies of public figures, particularly politicians, are also highlighted during key moments. Furthermore, the analysis reveals a gender bias, with women participating less in Wikipedia editing and content related to them being more frequently deleted. The study concludes that there is a need to promote greater diversity within the editing community and to implement further measures to mitigate biases on the platform. |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).