The effects of subjective norm on the intention to use social media networks : an exploratory study using PLS-SEM and machine learning approach

Al Kurdi, B; Alshurideh, M; Nuseir, M; Aburayya, A; Salloum, SA

Abstract

Several research has been conducted on social media application's acceptance, but factors that impact educational purposes are completely ignored in this research. Therefore, the research has been conducted with the purpose of developing a conceptual model, which is derived from the Technology Acceptance Model (TAM). The subjective norm of the study is to find out social media's acceptance in education by students. To find out the exact conclusion, the research follows the questionnaire survey method in which 310 questionnaires were distributed to the students of the United Arab Emirates' well-reputed university. In this questionnaire survey, two famous approaches were used to examine the collected data that is the partial least squares-structural equation modeling (PLS-SEM) and Machine Learning approach (ML). From the above-stated study, it has been observed that perceived usefulness, subjective norms, and perceived ease of use are proven to be significant measures of student's intention that motivates them to use social media networks for their educational purpose.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: International Conference on Advanced Machine Learning Technologies and Applications
• End Date: Mar 22, 2021
• Online Publication Date: Mar 5, 2021
• Deposit Date: Jun 22, 2021
• Journal: Advanced Machine Learning Technologies and Applications : proceedings of AMLTA 2021
• Electronic ISSN: 2194-5357
• Publisher: Springer
• Pages: 581-592
• Series Title: Advances in Intelligent Systems and Computing
• Series Number: 1339
• Book Title: Advanced Machine Learning Technologies and Applications : proceedings of AMLTA 2021
• ISBN: 9783030697167-(print);-9783030697174-(ebook)
• DOI: https://doi.org/10.1007/978-3-030-69717-4_55
• Publisher URL: https://doi.org/10.1007/978-3-030-69717-4_55
• Related Public URLs: https://doi.org/10.1007/978-3-030-69717-4
• Additional Information: Event Type : Conference