Influencers educativos en Twitter. Análisis de hashtags y estructura relacional

Educational influencers on Twitter. Analysis of hashtags and relationship structure

 Carlos Marcelo, Sevilla (España)

 Paula Marcelo, Sevilla (España)

https://doi.org/10.3916/C68-2021-06

Palabras clave

Activismo digital, análisis de redes sociales, aprendizaje informal, formación del profesorado, influencer, Twitter

Resumen

En este artículo indagamos acerca de los influencers educativos españoles con mayor presencia en Twitter: cuáles son los temas o hashtags más difundidos por ellos, las temáticas de sus intervenciones o qué tipo de red social configuran. Para dar respuesta a estos objetivos, en primer lugar, seleccionamos 54 docentes con alto nivel de seguidores. Analizamos y clasificamos los «hashtags» incluidos en un total de 106.130 tuits. El análisis de los hashtags nos ha mostrado que los temas más etiquetados corresponden a contenidos educativos en diferentes áreas del currículum, la colaboración, el intercambio y la difusión de materiales, documentos o recursos digitales, así como de acciones de formación o de debate sobre metodologías docentes innovadoras. Utilizando el programa Gephi hemos realizado un análisis de redes sociales, determinando el grado de centralidad y centralidad de intermediación de los 54 docentes, lo que nos ha permitido identificar influencers con mayor reconocimiento por parte del resto. A través del análisis de modularidad, hemos podido identificar cinco grupos de influencers que no funcionan como grupos cerrados, sino que mantienen frecuentes interacciones con el resto de influencers de otros grupos. A través de este estudio se pone de manifiesto la necesidad de conocer mejor los contenidos y procedimientos que pueden estar favoreciendo aprendizajes informales por parte de los docentes.

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Fundref

Esta investigación forma parte del proyecto titulado ¿Cómo aprenden los profesores en una sociedad conectada?, aprobado por el Plan Estatal 2017-2020, código PGC2018-096474-B-I00.

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Ficha técnica

Recibido: 04-11-2020

Revisado: 22-12-2020

Aceptado: 15-02-2021

OnlineFirst: 15-04-2021

Fecha publicación: 01-07-2021

Tiempo de revisión del artículo : 48 días | Media tiempo revisión número 68: 37 días

Tiempo de aceptación del artículo: 103 días | Media tiempo aceptación número 68: 78 días

Tiempo de edición del preprint: 193 días | Media tiempo edición número preprint 68: 168 días

Tiempo de edición del artículo: 238 días | Media tiempo edición número 68: 213 días

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