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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Detalles Bibliográficos
Autor: Boté-Vericad, Juan-José
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
Descripción
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.
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).