Carlos Barroso-Moreno, Complutense University of Madrid (Spain)
Laura Rayon-Rumayor, Complutense University of Madrid (Spain)
Antonio Bautista García-Vera, Complutense University of Madrid (Spain)
Keywords
Social network analysis, Big Data, education, disability, digital inclusion, influence groups
Abstract
Social media can contribute to an inclusive society, but they are also asymmetrical and polarised communication spaces. This requires competent teachers to build critical digital citizenship. The aim of this article is twofold: to present web scraping and text analytics as tools that define teachers' digital competences, and to investigate which posts on Twitter and Instagram are most viral in relation to education, disability and inclusion. A total of 48,991 publications in Spanish and English were analysed, corresponding to the period from 13 October 2021 to 1 May 2022. The 100 most viral posts were selected, and correlations were identified between the sentiment, gender and influence associated with the content, its temporal and geographic space. The results show that economic and political influence groups are the most viral, relegating non-profit organisations or individuals with altruistic outreach to second place; only on international days is this trend reversed. Bots do not interfere to impose messages; it is artificial intelligence algorithms that overshadow vindictive and humanistic content. The most influential people are predominantly male, associated with institutional accounts in the political sphere. It is concluded that Big Data and Business Intelligence tools help teachers to analyse relevant educational and social issues, and to acquire a collective ethic in the face of new educational challenges.
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Fundref
Technical information
Received: 29-05-2022
Revised: 21-06-2022
Accepted: 13-07-2022
OnlineFirst: 30-10-2022
Publication date: 01-01-2023
Article revision time: 23 days | Average time revision issue 74: 40 days
Article acceptance time: 45 days | Average time of acceptance issue 74: 69 days
Preprint editing time: 172 days | Average editing time preprint issue 74: 194 days
Article editing time: 217 days | Average editing time issue 74: 239 days
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Cited by
Cites in Web of Science
Barroso-Moreno, C; del Fresno-Garcia, M and Rayon-Rumayor, L. Inclusive employability and the role of social networks in digital society. A case study on Twitter, Instagram and YouTube Barroso-Moreno, C; del Fresno-Garcia, M and Rayon-Rumayor, L REVISTA ICONO 14-REVISTA CIENTIFICA DE COMUNICACION Y TECNOLOGIAS, 2023.
https://doi.org/10.7195/ri14.v21i2.2006
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Cites in Scopus
Barroso-Moreno, C., Rayón-Rumayor, L., Bañares-Marivela, E., Hernández-Ortega, J.. Polarization, virality and contrary sentiments for LGTB content on Instagram, TikTok, and Twitter), Profesional de la Informacion , .
Cites in Google Scholar
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How to cite
Barroso-Moreno, C., Rayon-Rumayor, L., & Bautista García-Vera, A. (2023). Big Data and Business Intelligence on Twitter and Instagram for digital inclusion. [Big Data y Business Intelligence en Twitter e Instagram para la inclusión digital]. Comunicar, 74, 49-60. https://doi.org/10.3916/C74-2023-04