What drives students' online self-disclosure behaviour on social media? A hybrid SEM and artificial intelligence approach
by Ibrahim Arpaci
International Journal of Mobile Communications (IJMC), Vol. 18, No. 2, 2020

Abstract: This study investigated drivers of the online self-disclosure behaviour on social media by employing a complementary structural equation modelling (SEM) and artificial intelligence approach. The study developed a theoretical model based on the 'theory of planned behaviour' (TPB) and 'communication privacy management' (CPM) theory. The predictive model was validated by employing a multi-analytical approach based on the data obtained from 300 undergraduate students. The model focused on the role of security, privacy, and trust perceptions in predicting the attitudes toward the selfie-posting behaviour. The results suggested that privacy and security are significantly associated with the trust, which explains a significant amount of the variance in the attitudes. Consistently, results of the machine-learning classification algorithms suggested that attributes of the security, privacy, and trust could predict the attitudes with an accuracy of more than 61%% in most cases. Further, mediation analysis results indicated that privacy has no direct effect, but an indirect effect on the attitudes. These findings suggested a trade-off between the privacy concerns and perceived benefits of the actual behaviour.

Online publication date: Mon, 09-Mar-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mobile Communications (IJMC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com