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Joanna Dyczkowska , Andrea Szirmai Madarasine & Adriana Tiron-Tud or, Development of Integrated Reporting in the SME Sector, Case Studies from European Countries, Springer, 2021
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Sitar-Tăut, D.A., Mican, D., Frömbling, L. & Sarstedt, M. (In press) Social Science Computer Review [Info Economics, Q1]

Autor: Ovidiu Ioan Moisescu

Publicat: 31 Decembrie 2021

Sitar-Taut, D.A., Mican, D., Frömbling, L. & Sarstedt, M. (In press) Digital Socialligators? Social Media-Induced Perceived Support During the Transition to the COVID-19 Lockdown. Social Science Computer Review.


✓ Publisher: Sage
✓ Categories: Computer Science, Interdisciplinary Applications; Information Science & Library Science; Social Sciences, Interdisciplinary
✓ Article Influence Score (AIS): 1.763 (2020) / Q1 in all categories

Journal ranked:
#9 in Social Sciences, Interdisciplinary
#11 in Information Science & Library Science
#12 in Computer Science, Interdisciplinary Applications

Abstract: The sudden COVID-19-induced transition from a physical university life to a virtual one was a painful one for many students. Social distancing measures mean more than a simple change from face-to-face to online education. This study investigates how different social aspects, such as the students’ psychological sense of community, social capital, and use of social media, facilitated the perceived social support during the transition to the COVID-19 lockdown. Our results not only underline social media’s role, but also indicate that the perceived social support, as well as the bonding and bridging social capital, were particularly relevant during the transition process. Our findings are aimed at organizational management by recommending actionable ways in which they could improve social support by organizing computer-supported social networks, social support predictors, and specialized interventions for students with less perceived social support. As such, the study provides unique insights into the COVID-19-induced lockdown situation among students, while offering a transition model that also generalizes to other settings.

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