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Social media users and cybersecurity awareness: predicting self-disclosure using a hybrid artificial intelligence approach

Naurin Farooq Khan (Faculty of Computing, Riphah International University, Islamabad, Pakistan)
Naveed Ikram (Faculty of Computing, Riphah International University, Islamabad, Pakistan)
Hajra Murtaza (Faculty of Computing, Riphah International University, Islamabad, Pakistan)
Muhammad Aslam Asadi (Bahauddin Zakariya University, Multan, Pakistan)

Kybernetes

ISSN: 0368-492X

Article publication date: 28 October 2021

Issue publication date: 17 January 2023

436

Abstract

Purpose

This study aims to investigate the cybersecurity awareness manifested as protective behavior to explain self-disclosure in social networking sites. The disclosure of information about oneself is associated with benefits as well as privacy risks. The individuals self-disclose to gain social capital and display protective behaviors to evade privacy risks by careful cost-benefit calculation of disclosing information.

Design/methodology/approach

This study explores the role of cyber protection behavior in predicting self-disclosure along with demographics (age and gender) and digital divide (frequency of Internet access) variables by conducting a face-to-face survey. Data were collected from 284 participants. The model is validated by using multiple hierarchal regression along with the artificial intelligence approach.

Findings

The results revealed that cyber protection behavior significantly explains the variance in self-disclosure behavior. The complementary use of five machine learning (ML) algorithms further validated the model. The ML algorithms predicted self-disclosure with an area under the curve of 0.74 and an F1 measure of 0.70.

Practical implications

The findings suggest that costs associated with self-disclosure can be mitigated by educating the individuals to heighten their cybersecurity awareness through cybersecurity training programs.

Originality/value

This study uses a hybrid approach to assess the influence of cyber protection behavior on self-disclosure using expectant valence theory (EVT).

Keywords

Citation

Khan, N.F., Ikram, N., Murtaza, H. and Asadi, M.A. (2023), "Social media users and cybersecurity awareness: predicting self-disclosure using a hybrid artificial intelligence approach", Kybernetes, Vol. 52 No. 1, pp. 401-421. https://doi.org/10.1108/K-05-2021-0377

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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