Published date: Feb 01 2023

Journal Title: KnE Social Sciences

Issue title: Economies of the Balkan and Eastern European Countries (EBEEC)

Pages: 360–374

DOI: 10.18502/kss.v8i1.12656

Lambros Tsourgiannisltsourgiannis@gmail.comDirectorate of Public Health and Social Care of Regional District of Xanthi, Region of Eastern Macedonia and Thrace, Headquarters Xanthi, Greece

Stavros ValsamidisInternational Hellenic University, Department of Accounting and Finance, Campus of Kavala, 65404 Kavala Greece

Polina KaragianniHellenic Army General Staff, 4

Konstantinos TassosHellenic Army General Staff, 4

Human civilization has been transformed dramatically due to the increase of information and communication technologies (ICTs). The new digital era, and more particularly the digitization of information has contributed to many changes in all areas of life. More specifically the social relations among people developed new social and cultural structures. Furthermore, the COVID-19 pandemic forced humanity to adopt digital technologies in most aspects of economic and social life. Internet, telework, remote work, and distance learning are now part of everyday life in society, and users of online social networks have increased dramatically in comparison with those of recent decades around the world. On the other hand, the situation that human experience due to the pandemic produced by COVID-19 disease may have increased the negative effects of excessive use of social networks. This study aims to explore the attitudes of Greek citizens toward the use of the Internet and social media before and during the pandemic. A primary survey on random 525 Greek citizens was conducted from September–November 2021. Principal component analysis (PCA) was conducted to identify the main attitudes of Greek citizens toward the use of social media during COVID-19 era. Therefore, two main attitudes were derived from PCA: (a) use of social media to be informed, and (b) use of social media for entertainment. Cluster analysis was performed to classify those citizens into groups according to their attitudes toward the use of social networks during COVID-19 period. It identified three groups of citizens: (a) those who are indifferent to the use of social networks (b) those who use social networks mainly to be informed, and (c) those who use social networks only for entertainment. Following that, a Friedman nonparametric test was performed to determine the primary reasons why Greek citizens use the Internet and social networks prior to and during the COVID-19 pandemic. Nonparametric tests, including the Chi-square and Friedman nonparametric tests were performed to develop the profile of each of the identified groups of citizens toward the main reasons they use the Internet and social networks, for what purposes, and their demographic characteristics.

Keywords: social networks, Internet, COVID-19

[1] Abd-Alrazaq A, Alhuwail D, Househ M, Hamdi M, Shah Z. Top concerns of tweeters during the COVID-19 pandemic: Infoveillance study. Journal of Medical Internet Research. 2020;22(4):e19016.

[2] Arab E, Díaz A. Impacto de las redes sociales e internet en la adolescencia: Aspectos positivos y negativos. Revista Médica Clínica. 2015;26:7–13.

[3] Bavel JJV, Baicker K, Boggio PS, Capraro V, Cichocka A, Cikara M. Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behaviour. 2020;4(5):460–471.

[4] Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ, USA: Erlbaum; 1988. p. 273–406.

[5] Elmer T, Mepham K, Stadtfeld C. Students under lockdown: Comparisons of students’ social networks and mental health before and during the COVID-19 crisis in Switzerland. Plos ONE. 2020;15(7):e0236337.

[6] ELSTAT. Demographic characteristics / 2011. 2020. Available from: https://www.statistics.gr/el/statistics/-/publication/SAM03/

[7] Faul F, Erdfelder E, Buchner A, Lang A. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods. 2009;41(4):1149–1160.

[8] Gómez-Galán J. New perspectives on integrating social networking and Internet communications in the curriculum. eLearning Pap. 2011;26:1–7.

[9] Gómez-Galán J, Martinez – Lopez JA, Lazaro-Perez C, Sanchez-Serrano JLS. Social Networks consumption and addiction in college students during the COVID-19 pandemic: Educational approach to responsible use. Sustainability. 2020;12:7737.

[10] Gómez-Galán J, Vergara D, Ordóñez-Olmedo E, Veytia MG. Time of use and patterns of Internet consumption in university students: A comparative study between Spanish-speaking countries. Sustainability. 2020;12:5087.

[11] González-Padilla DA, Tortolero-Blanco L. Social media influence in the COVID-19 Pandemic. International Brazilian Journal of Urology. 2020;46:120–124.

[12] Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate data analysis. New Jersey: Prentice Hall Inc.; 1998.

[13] Jalali M., Bouyer A. Exploring the relationship of university students’ educational variables and the degree of their use of virtual social networks. Information Discovery and Delivery. 2019;47:182–191.

[14] Kaya T. The changes in the effects of social media use of Cypriots due to COVID-19 pandemic. Technology in Society. 2020;63:101380.

[15] Khanday AMUD, Khan QR, Rabani ST. Identifying propaganda from online social networks during COVID-19 using machine learning techniques. International Journal of Information Technology. 2021;13(1):115–122.

[16] Kovacs B, Caplan N, Grob S, King M. Social networks and loneliness during the COVID-19 pandemic. Socius. 2021;7.

[17] Li C, Chen LJ, Chen X, Zhang M, Pang CP, Chen H. Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020. Eurosurveillance. 2020;25(10):2000199.

[18] Lim J, Richardson JC. Exploring the effects of students’ social networking experience on social presence and perceptions of using SNSs for educational purposes. Internet and Higher Education. 2016;29:31–39.

[19] Mese C, Aydin GS. The use of social networks among university students. Educational Research and Reviews. 2019;14:190–199.

[20] Mouratidis K, Papagiannakis A. COVID-19, internet, and mobility: The rise of telework, telehealth, e-learning, and e-shopping. Sustainable Cities and Society. 2021;74:103182.

[21] Oppenheim AN. Questionnaire design, interviewing and attitude measurement. New York: Bloomsbury Publishing; 2000.

[22] Papouli E, Chatzifotiou S, Tsairidis C. The use of digital technology at home during the COVID-19 outbreak: Views of social work students in Greece. Social Work Education. 2020;39(8):1107–1115.

[23] Siardos G. Methodology of agricultural sociological research. Thessaloniki, Greece: Ziti Publications; 1997. 367 p.

[24] Tsourgiannis L, Delias P, Polychronidou P, Karasavvoglou A, Valsamidis S. Profiling tourists who have holidays in the region of eastern Macedonia and Thrace in Greece. Procedia Economics and Finance. 2015;33:450–460.

[25] Vahdat-Nejad H, Salmani F, Hajiabadi M, Azizi F, Abbasi S, Jamalian M, et al. Extracting feelings of people regarding COVID-19 by social network mining. Journal of Information & Knowledge Management. 2022;21(1):2240008.

[26] Wu Y, Xie L, Huang S, Li P, Yuan Z, Liu W. Using social media to strengthen public awareness of wildlife conservation. Ocean & Coastal Management. 2018;153:76–83.

[27] Yang S, Fichman P, Zhu X, Sanfilippo M, Li S, Fleischmann KR. The use of ICT during COVID-19. Proceedings of the Association for Information Science and Technology. 2020;57(1):e297.

[28] Zikmund WG, Babin BJ, Carr JC, Griffin M. Business research methods. Cengage Learning; 2013.

[29] Mourad A, Srour A, Harmanani H, Jenainati C, Arafeh M. Critical impact of social networks infodemic on defeating coronavirus COVID-19 pandemic: Twitterbased study and research directions. IEEE Transactions on Network and Service Management. 2020;17(4):2145–2155.

[30] Ofcom. News consumption in the UK. 2019. Available from: https://www.ofcom.org.uk/