Information and source credibility towards information adoption amongst upper secondary school students
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THE EFFECTS OF INFORMATION QUALITY AND SOURCE CREDIBILITY TOWARDS INFORMATION ADOPTION THROUGH INFORMATION USEFULNESS AMONGST HIGH SCHOOL STUDENTS IN SURABAYA downloads: 0
THE EFFECT OF INFORMATION QUALITY AND SOURCE CREDIBILITY TOWARDS INFORMATION ADOPTION THROUGH INFORMATION USEFULNESS AMONGST THE HIGH SCHOOL STUDENTS IN SURABAYA downloads: 0
Keywords:
adoption information model, twitter, social media
Abstract
The purpose of this study was to determine the extent to which the information quality and source credibility affect the use and the process of information adoption, especially among upper secondary school students as Twitter users who are prone to hoaxes and fake news. Research subject and method: The stratified sample was 100 upper secondary school students in Surabaya who used Twitter and had read or followed threads. The respondents were asked questions to test their dependence on Twitter and their social media behaviour that affected the information adoption process. Information quality has a significant effect on usability, in contrast to source credibility which does not affect the usefulness of information; however, these two dependent variables have a strong relationship which intervenes in the information adoption process among upper secondary school students.
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Boyd, D., Golder, S., & Lotan, G. (2010). Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. Proceedings of the Annual Hawaii International Conference on System Sciences. https://doi.org/10.1109/HICSS.2010.412
Castillo, C., Mendoza, M., & Poblete, B. (2011). Information credibility on Twitter. Proceedings of the 20th International Conference Companion on World Wide Web, WWW 2011, 675–684. https://doi.org/10.1145/1963405.1963500
Donald, B. (2016). Stanford researchers find students have trouble judging the credibility of information online. Stanford Graduate School of Education, 1–4.
Ghozali, I. (2013). Aplikasi Analisis Multivariate dengan Program IBM SPSS 21 Update PLS Regresi (7th ed.). Semarang : Badan Penerbit Universitas Diponegoro.
Go, A., Bhayani, R., & Huang, L. (2009). Twitter Sentiment Classification using Distant Supervision. Processing, 1–6.
Irena, B., & Erwin Budi Setiawan. (2020). Fake News (Hoax) Identification on Social Media Twitter using Decision Tree C4.5 Method. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 4(4), 711–716. https://doi.org/10.29207/resti.v4i4.2125
Jeri-Yabar, A., Sanchez-Carbonel, A., Tito, K., Ramirez-delCastillo, J., Torres-Alcantara, A., Denegri, D., & Carreazo, Y. (2019). Association between social media use (Twitter, Instagram, Facebook) and depressive symptoms: Are Twitter users at higher risk? International Journal of Social Psychiatry, 65(1), 14–19. https://doi.org/10.1177/0020764018814270
Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), 241–251. https://doi.org/10.1016/j.bushor.2011.01.005
Kriscautzky, M., & Ferreiro, E. (2014). The credibility of information on the Internet: Criteria stated and criteria used by Mexican students. Educacao e Pesquisa, 40(4), 913–934. https://doi.org/10.1590/s1517-97022014121511
Li, R., & Suh, A. (2015). Factors Influencing Information credibility on Social Media Platforms: Evidence from Facebook Pages. Procedia Computer Science, 72, 314–328. https://doi.org/10.1016/j.procs.2015.12.146
Mcleod, R. (2008). Management Information Systems Chapter 8. In Management Information Systems.
Morissan, M. (2020). Hubungan penggunaan smartphone dan kinerja akademik di kalangan mahasiswa. Jurnal Studi Komunikasi 4 (1). https://doi.org/10.25139/jsk.v4i1.1800
Pal, D., Vanijja, V., Arpnikanondt, C., Zhang, X., & Papasratorn, B. (2019). A quantitative approach for evaluating the quality of experience of smart-wearables from the quality of data and quality of information: An end user perspective. IEEE Access, 7, 64266–64278. https://doi.org/10.1109/ACCESS.2019.2917061
Power, A. (2014). What is social media? British Journal of Midwifery, 22(12), 896–897. https://doi.org/10.12968/bjom.2014.22.12.896
Prod, P. K. (2017). Pengaruh Kualitas Produk, Harga Dan Promosi Terhadap Keputusan Pembelian Mobil Nissan X-Trail Pada Pt. Wahana Wirawan Manado. Jurnal EMBA: Jurnal Riset Ekonomi, Manajemen, Bisnis Dan Akuntansi, 5(2). https://doi.org/10.35794/emba.v5i2.16521
Putra, E. D. (2014). Menguak Jejaring Sosial. 108.
Shariff, S. M., Zhang, X., & Sanderson, M. (2017). On the credibility perception of news on Twitter: Readers, topics and features. Computers in Human Behavior, 75, 785–796. https://doi.org/10.1016/j.chb.2017.06.026
Siswoyo, H. (2012). Structural Equation Modeling. Bekasi: PT Intermedia Personalia Utama. https://doi.org/10.4135/9781412983907.n1909
Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47–65. https://doi.org/10.1287/isre.14.1.47.14767
Taprial, V., & Kanwar, P. (n.d.). Understanding.
Unaradjan, D. D., & Sihotang, K. (2019). Metode Penelitian Kuantitatif. Jakarta: Penerbit Unika Atma Jaya Jakarta.
Vosoughi, S., Roy, D., & Aral, S. (2018). News On-line. Science, 1151(March), 1146–1151.
Watie, E. D. S. (2016). Komunikasi dan Media Sosial (Communications and Social Media). Jurnal The Messenger, 3(2), 69. https://doi.org/10.26623/themessenger.v3i2.270
Yang, J., Yu, M., Qin, H., Lu, M., & Yang, C. (2019). A twitter data credibility framework—Hurricane Harvey as a use case. ISPRS International Journal of Geo-Information, 8(3). https://doi.org/10.3390/ijgi8030111
Zhu, D. H., Chang, Y. P., & Luo, J. J. (2016). Understanding the influence of C2C communication on purchase decision in online communities from a perspective of information adoption model. Telematics and Informatics, 33(1), 8–16. https://doi.org/10.1016/j.tele.2015.06.001
