Unlocking the potential of data: datification in educational research using social listening methodology
Datafication revolutionizes the way data is collected and analyzed on social media platforms, with a special focus on education. This study has a twofold objective: to implement advanced Big Data and Business Intelligence techniques to evaluate their effectiveness in social listening and to analyze behavioral patterns of social networks for educational content. A consortium of researchers from various universities (Complutense University of Madrid, National University of Distance Education and Rey Juan Carlos University) have investigated more than two million posts on Instagram, Twitter, TikTok and YouTube related to education, disability and inclusion topics since 2021. The results show how algorithms and groups with high levels of influence dominate the platform, potentially affecting the visibility of altruistic content. Additionally, a trend towards the commercialization of inclusive employability is identified, which may obscure non-profit broadcasts. The findings suggest that these data analysis techniques may be crucial to tailoring educational strategies that promote informed and responsible digital citizenship. This research supports the development of educational practices that integrate a collective ethical perspective, addressing educational challenges in an inclusive and effective manner. The educational community has a role to play in fostering critical digital literacy that is not guided by market logic.
Authors
- Carlos Barroso-Moreno (ORCID: https://orcid.org/0000-0002-1609-2267)
- Laura Rayón Rumayor (ORCID: https://orcid.org/0000-0003-0339-8221)
- Elena Bañares-Marivela (ORCID: https://orcid.org/0000-0002-9384-0193)
- Ana María de las Heras Cuenca (ORCID: https://orcid.org/0000-0001-5259-1218)
Institutions
- Universidad Complutense de Madrid (ES)
Publication Details
- Published
- 2024-09-18
- DOI
- https://doi.org/10.1145/3702163.3702441
- Primary Topic
- Social Media and Politics
- Type
- article
- Field-Weighted Citation Impact
- 0.00