Abstract: Securing a nation is more complicated in modern days than how it was decades ago. In the era of big data, massive information is constantly being shared in cyberspace. Online rumours and fake news could evoke negative emotions and disruptive behaviours that possibly can jeopardize national security. Real-time detection and monitoring of unsettling emotions and potential national security threats should be further developed to help authorities manage the situation early. Text in the online news could be weighted with emotions that possibly lead to a misunderstanding that can affect national security and trigger chaos. Thus, understanding the emotion included in the online news and the relationship with national security is crucial. Kansei approach was determined as a methodology capable of interpreting human emotions towards an artefact. This research explores the emotion assessment using Kansei for text in online news and summarized the emotion variable factors that are likely to have a relationship with an individual state of mind towards one of the national security elements which are political security. The result determines that the identified variables of factors were “Frustrated,” Consent,” Resentful” and “Attentive”. This gives an understanding of the significant effect of people's emotions represented in the text for political security elements.

Noor Afiza Mat Razali, Nur Atiqah Malizan, Nor Asiakin Hasbullah, Norul Zahrah Mohd Zainuddin, Normaizeerah Mohd Noor, Khairul Khalil Ishak and Sazali Sukardi, “Assessment of Emotion in Online News based on Kansei Approach for National Security” International Journal of Advanced Computer Science and Applications(IJACSA), 12(7), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120741

@article{Razali2021,
title = {Assessment of Emotion in Online News based on Kansei Approach for National Security},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120741},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120741},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {7},
author = {Noor Afiza Mat Razali and Nur Atiqah Malizan and Nor Asiakin Hasbullah and Norul Zahrah Mohd Zainuddin and Normaizeerah Mohd Noor and Khairul Khalil Ishak and Sazali Sukardi}
}