Kala Devi Managuran, Kasturi Dewi Varathan, Mohammad Ali Derhem Al-Garadi
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CAN MUSIC LIKES IN FACEBOOK DETERMINE YOUR PERSONALITY?
The ‘like’ icon is the most frequently used among all icons on Facebook. Although this social media platform is used by many people to express their music preferences publicly, Facebook ‘likes’ are still underutilised in determining personality. Thus, music ‘likes’ was employed in this study to gauge the personality of individuals based on a model that was developed by mapping music genres and personality traits. A computational technique that gauges users’ personalities on the basis of their music ‘likes’ on Facebook was also introduced. Results discovered that personality traits based on music preferences on Facebook assisted in revealing the personality of individuals. Furthermore, similar patterns in personality traits were obtained from a manual test, i.e., the Big Five inventory test performed on each respondent. Music genres and personality traits were mapped by the proposed model to examine the relationship between these two variables and the findings revealed that music ‘likes’ can be utilised to identify the personality of individuals.
期刊介绍:
The Malaysian Journal of Computer Science (ISSN 0127-9084) is published four times a year in January, April, July and October by the Faculty of Computer Science and Information Technology, University of Malaya, since 1985. Over the years, the journal has gained popularity and the number of paper submissions has increased steadily. The rigorous reviews from the referees have helped in ensuring that the high standard of the journal is maintained. The objectives are to promote exchange of information and knowledge in research work, new inventions/developments of Computer Science and on the use of Information Technology towards the structuring of an information-rich society and to assist the academic staff from local and foreign universities, business and industrial sectors, government departments and academic institutions on publishing research results and studies in Computer Science and Information Technology through a scholarly publication. The journal is being indexed and abstracted by Clarivate Analytics'' Web of Science and Elsevier''s Scopus