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 ORCID: https://orcid.org/0000-0002-0825-4617, Alshurideh, M, Nuseir, M ORCID: https://orcid.org/0000-0002-1319-5404, Aburayya, A ORCID: https://orcid.org/0000-0002-1428-0547 and Salloum, SA ORCID: https://orcid.org/0000-0002-6073-3981 2021, The effects of subjective norm on the intention to use social media networks : an exploratory study using PLS-SEM and machine learning approach , in: International Conference on Advanced Machine Learning Technologies and Applications, 20th-22nd March 2021, Cairo, Egypt.

Full text not available from this repository. (Request a copy)

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.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Advanced Machine Learning Technologies and Applications : proceedings of AMLTA 2021
Publisher: Springer
Series Name: Advances in Intelligent Systems and Computing
ISBN: 9783030697167 (print); 9783030697174 (ebook)
ISSN: 2194-5357
Related URLs:
Depositing User: USIR Admin
Date Deposited: 22 Jun 2021 13:22
Last Modified: 27 Aug 2021 21:54
URI: http://usir.salford.ac.uk/id/eprint/61010

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)