A. Conde Sánchez, S. M. Jiménez Zafra, M. T. Martín Valdivia, A. J. Sáez Castillo

La viralidad en Twitter es un fenómeno que está llamando la atención de investigadores de diferentes áreas. Se han realizado varios trabajos para determinar qué factores aumentan o disminuyen la probabilidad de retuitear. En este trabajo, presentamos un estudio estadístico basado en el modelo de regresión Waring para datos de conteo que muestra cómo los términos que expresan sentimientos, es decir, palabras negativas o positivas, afectan a la probabilidad de ser retuiteado. En concreto, nos hemos centrado en la situación política española durante el pseudo referéndum celebrado en Cataluña el 1 de octubre de 2017. Hemos encontrado que el uso de la negatividad en un tweet aumenta la probabilidad de ser retuiteado. Por el contrario, los tuits con más positividad disminuye esta probabilidad. Para determinar la negatividad y la positividad de los tweets hemos utilizado varios recursos lingüísticos, comprobando que el lexicon de iSOL es el más adecuado.

Keywords: Regresión de Waring generalizada, datos de conteo, viralidad, Twitter

Scheduled

Posters III
June 9, 2022  10:10 AM
Faculty Hall


Other papers in the same session

FMM package: a proposal to analyze oscillatory signals in R

I. Fernández Martínez, A. Rodríguez Collado, Y. Larriba, C. Canedo, C. Rueda

Influencia de la sobrevaloración en los índices contextuales de PISA

C. E. Carleos Artime, N. Corral Blanco, S. Álvarez Morán

La realidad del turismo en España tras la pandemia

I. Jiménez Manchado, R. M. Espejo Montes

Método de agrupación automática de Ward para partes de una composición (R-mode)

J. A. Martín Fernández, V. Di Donato, V. Pawlowsky-Glahn, J. J. Egozcue

Gender inequality in Ecuador using poverty measures in RDS

I. Sánchez Borrego, M. M. M. Rueda García, H. Mullo Guaminga


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