Social Networks in Military Powers: Network and Sentiment Analysis during the COVID-19 Pandemic

Author:

Quilez-Robres Alberto1ORCID,Acero-Ferrero Marian2ORCID,Delgado-Bujedo Diego3,Lozano-Blasco Raquel2ORCID,Aiger-Valles Montserrat2

Affiliation:

1. Science Education Department, Zaragoza University, 22003 Huesca, Spain

2. Psychology and Sociology Department, Zaragoza University, 50009 Zaragoza, Spain

3. Ejército de Tierra (Ministerio de Defensa), Regimiento de Ingenieros N°1, 09193 Burgos, Spain

Abstract

The outbreak of the COVID-19 pandemic shifted socialization and information seeking to social media platforms. The armed forces of the major military powers initiated civil support operations to combat the invisible and common enemy. The aim of this study is to analyze the existence of differential behavior in the corporate profiles of the major military powers on Twitter, Instagram, and Facebook during the COVID-19 pandemic. The principles of social network analysis were followed, along with sentiment analysis, to study web positioning and the emotional content of the posts (N = 25,328). The principles of data mining were applied to process the KPIs (Fanpage Karma), and an artificial intelligence (meaning cloud) sentiment analysis was applied to study the emotionality of the publications. The analysis was carried out using the IBM SPSS Statistics 25 statistical software. Subsequently, a qualitative content analysis was carried out using frequency graphs or word clouds (the application “nubedepalabras” used in English). Significant differences were found between the behavior on social media and the organizational and communicative culture of the nations. It is highlighted that some nations present different preferences from the main communicative strategy developed by their armed forces. Corporate communication of the major military powers should consider the emotional nature of their posts to align with the preferences of their population.

Publisher

MDPI AG

Subject

Applied Mathematics,Modeling and Simulation,General Computer Science,Theoretical Computer Science

Reference63 articles.

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