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Students’ Intention to Share Information Via Social Media: A Case Study of Covid-19 Pandemic
Abstract
Agility of science and technology in communication has brought a new dimension of information dissemination, which may have influenced human perceptions, especially on the dissemination of news pertaining to this pandemic. This research aims to determine the students’ sources of information regarding the COVID-19 disease and investigate their intention to share the information pertaining to COVID-19. A survey study was designed using an online questionnaire involving 147 higher education students. The online questionnaire; measures three elements of the students’ intention, namely initiative, desire and resourcefulness. The findings; the sources of information regarding the COVID-19 pandemic are mainly the government authorities and local healthcare workers. The most preferred medium of information regarding the COVID-19 pandemic is social media, and the most trusted medium is the television broadcast. Also, finding suggests that the students take initiative to verify information and demonstrate a desire to share credible and right information with their family and friends through social media. As such, in an effort or attempt to disseminate credible information about any important matters to the general public, the government can count on students as agents for transmitting the information to third parties including their family and friends.
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Boukes, M. (2019). Social network sites and acquiring current affairs knowledge: The impact of Twitter and Facebook usage on learning about the news. Journal of Information Technology and Politics, 16(1), 36-51.
Bora, K., Das, D., Barman, B., & Borah, P. (2018). Are internet videos useful sources of information during global public health emergencies? A case study of YouTube videos during the 2015–16 Zika virus pandemic. Pathogens and global health, 112(6), 320-328.
Confessore, G. J., & Park, E. (2004). Factor validation of the learner autonomy profile, version 3.0 and extraction of the short form. International Journal of Self-Directed Learning, 1(1), 39-58.
Dehghani, R., & Keyvani, F. (2019). The role of ICT information technology on the development of the interaction of Folks and religions in the countries multi nation, based on the matrix evaluation model SWOT. Academic Scientific Journals, 42, 324-336.
Elfil, M., & Negida, A. (2017). Sampling methods in clinical research; an educational review. Emergency (Tehran, Iran), 5(1), e52.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Philippines: Addison-Wesley Publishing Company.
Garrett, L. (2020). COVID-19: the medium is the message. The Lancet, 395(10228), 942-943.
Hickey, J. E., Gagnon, A. J., & Jitthai, N. (2016). Knowledge about pandemic influenza preparedness among vulnerable migrants in Thailand. Health Promotion International, 31(1), 124-132.
https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports, retrieved on March 17, 2020.
Krejcie, R.V., & Morgan, D.W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30, 607-610.
Ko, H. C. (2018). Social desire or commercial desire? The factors driving social sharing and shopping intentions on social commerce platforms. Electronic Commerce Research and Applications, 28, 1-15.
Luth, W., Jardine, C., & Bubela, T. (2013). When pictures waste a thousand words: analysis of the 2009 H1N1 pandemic on television news. PloS one, 8(5), e64070.
Liou, D. K., Chih, W. H., Hsu, L. C., & Huang, C. Y. (2016). Investigating information sharing behavior: the mediating roles of the desire to share information in virtual communities. Information Systems and e-Business Management, 14(2), 187-216.
Meier, K., Glatz, T., Guijt, M. C., Piccininni, M., van der Meulen, M., Atmar, K., Jolink, A.T.C., Kurth, T., Rohmann, J.L., Najafabadi, A.H.Z. (2020). COVID-19 Survey Study group. Public perspectives on social distancing and other protective measures in Europe: a cross-sectional survey study during the COVID-19 pandemic. medRxiv. https://www.medrxiv.org/content/10.1101/2020.04.02.20049676v1.full.pdf+html, retrieved on March 17, 2020.
McNeill, A., Harris, P. R., & Briggs, P. (2016). Twitter influence on UK vaccination and antiviral uptake during the 2009 H1N1 pandemic. Frontiers in Public Health, 4, 26.
Ordóñez, K., Vázquez, A. I. R., & Suing, A. (2019). Internet and Local Television in the Context of Digital Transformation. World Conference on Information Systems and Technologies (pp. 433-439). Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-030-16187-3_42, retrieved on March 17, 2020.
Perera, R., & Heneghan, C. (2008). D, Badenoch. Statistics toolkit, Blackwell Publishing: Massachusetts.
Schimmenti, A., Billieux, J., & Starcevic, V. (2020). The four horsemen of fear: An integrated model of understanding fear experiences during the COVID-19 pandemic. Clinical Neuropsychiatry, 17(2), 41-45.
Strekalova, Y. A. (2017). Health risk information engagement and amplification on social media: News about an emerging pandemic on Facebook. Health Education and Behavior, 44(2), 332-339.
Višňovský, J., Gregus, Ľ., Mináriková, J., & Kubíková, K. (2019). Television News As An Information Source And Its Perception In Slovakia. Communication Today, 10(1), 40-61.
Wright, K. B. (2005). Researching Internet-based populations: Advantages and disadvantages of online survey research, online questionnaire authoring software packages, and web survey services. Journal of Computer-mediated Communication, 10(3), JCMC1034.
DOI: https://doi.org/10.17509/ijost.v5i2.24586
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