Predicting the Intention to Use Social Media Sites: A Hybrid SEM - Machine Learning Approach-Reference-Cited by-同舟云学术

Predicting the Intention to Use Social Media Sites: A Hybrid SEM - Machine Learning Approach

Published:2021 Issue: Volume: Page:324-334
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Salloum Said A.^ORCID,AlAhbabi Nafla Mahdi Nasser^ORCID,Habes Mohammed^ORCID,Aburayya Ahmad^ORCID,Akour Iman^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-69717-4_32

Reference36 articles.

1. Salloum, S.A., Al-Emran, M., Monem, A., Shaalan, K.: A survey of text mining in social media: Facebook and Twitter perspectives. Adv. Sci. Technol. Eng. Syst. J. 2(1), 127–133 (2017)

2. Al-Qaysi, N., Al-Emran, M.: Code-switching usage in social media : a case study from Oman. Int. J. Inf. Technol. Lang. Stud. 1(1), 25–38 (2017)

3. Salloum, S.A., Mhamdi, C., Al Kurdi, B., Shaalan, K.: Factors affecting the adoption and meaningful use of social media: a structural equation modeling approach. Int. J. Inf. Technol. Lang. Stud. 2(3), 96–109 (2018)

4. Salloum, S.A., Maqableh, W., Mhamdi, C., Al Kurdi, B., Shaalan, K.: Studying the social media adoption by university students in the United Arab Emirates. Int. J. Inf. Technol. Lang. Stud. 2(3), 83–95 (2018)

5. Alghizzawi, M., Salloum, S.A., Habes, M.: The role of social media in tourism marketing in Jordan. Int. J. Inf. Technol. Lang. Stud. 2(3), 59–70 (2018)

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