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DOI: 10.14569/IJACSA.2021.0121005
PDF

Visual Selective Attention System to Intervene User Attention in Sharing COVID-19 Misinformation

Author 1: Zaid Amin
Author 2: Nazlena Mohamad Ali
Author 3: Alan F. Smeaton

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 10, 2021.

  • Abstract and Keywords
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Abstract: Information sharing on social media must be accompanied by attentive behavior so that in a distorted digital environment, users are not rushed and distracted in deciding to share information. The spread of misinformation, especially those related to the COVID-19, can divide and create negative effects of falsehood in society. Individuals can also cause feelings of fear, health anxiety, and confusion in the treatment COVID-19. Although much research has focused on understanding human judgment from a psychological underline, few have addressed the essential issue in the screening phase of what technology can interfere amidst users' attention in sharing information. This research aims to intervene in the user's attention with a visual selective attention approach. This study uses a quantitative method through studies 1 and 2 with pre-and post-intervention experiments. In study 1, we intervened in user decisions and attention by stimulating ten information and misinformation using the Visual Selective Attention System (VSAS) tool. In Study 2, we identified associations of user tendencies in evaluating information using the Implicit Association Test (IAT). The significant results showed that the user's attention and decision behavior improved after using the VSAS. The IAT results show a change in the association of user exposure, where after the intervention using VSAS, users tend not to share misinformation about COVID-19. The results are expected to be the basis for developing social media applications to combat the negative impact of the infodemic COVID-19 misinformation.

Keywords: Visual selective attention; COVID-19 misinformation; user attention; information sharing; implicit association test

Zaid Amin, Nazlena Mohamad Ali and Alan F. Smeaton, “Visual Selective Attention System to Intervene User Attention in Sharing COVID-19 Misinformation” International Journal of Advanced Computer Science and Applications(IJACSA), 12(10), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121005

@article{Amin2021,
title = {Visual Selective Attention System to Intervene User Attention in Sharing COVID-19 Misinformation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121005},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121005},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {10},
author = {Zaid Amin and Nazlena Mohamad Ali and Alan F. Smeaton}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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