Abstracts
Résumé
S’appuyant sur un ensemble de données de 829 résumés et titres publiés de la revue Management international de 2009 à 2023, cet article présente un cadre de détection des communautés pour décoder les complexités des données textuelles non structurées. En employant des outils d’analyse de la science des données, il dévoile des groupes thématiques cachés, offrant une nouvelle perspective sur la collaboration et l’évolution des auteurs de la revue. L’approche met en évidence des étapes importantes telles que le prétraitement et la visualisation des données. Grâce à des informations exploitables, cette étude améliore non seulement le cadre thématique de la revue, mais fournit également une feuille de route stratégique pour l’évolution éditoriale.
Mots-clés :
- détection des communautés,
- théorie des graphes,
- réseaux bipartites,
- visualisation des réseaux,
- dynamique de la collaboration,
- analyse temporelle
Abstract
This second research note draws from the same dataset of 829 abstracts and papers published by the journal over the period in question to formulate a community detection framework capable of decoding unstructured textual data, notwithstanding the complexities thereof. Using data science analysis tools, the research note discovers a number of hidden thematic groups, thereby spawning new perspectives on the various ways that journal authors have collaborated and evolved over this period. Several significant phases are identified, including data pre-processing and visualisation. Both research notes offer actionable insights and lay out a strategic roadmap enabling further editorial development.
Keywords:
- graph theory,
- bipartite networks,
- network visualisation,
- collaboration dynamics,
- temporal analysis
Resumen
Basándose en el mismo conjunto de datos de 829 resúmenes y títulos publicados en la revista Gestión Internacional entre 2009 y 2023, este informe de investigación presenta un marco de detección de comunidades para decodificar las complejidades de los datos textuales no estructurados. Al emplear herramientas de análisis de la ciencia de datos, se descubren grupos temáticos ocultos, proporcionando una nueva perspectiva sobre la colaboración y la evolución de los autores de la revista. El enfoque destaca pasos importantes como el preprocesamiento y la visualización de datos. Gracias a la información procesable, estos dos informes de investigación proporcionan una hoja de ruta estratégica para la evolución editorial.
Palabras clave:
- detección de comunidades,
- teoría de grafos,
- redes bipartitas,
- visualización de redes,
- dinámica de colaboración,
- análisis temporal
Appendices
Bibliographie
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