Web mining in classifying youth emotions / Zura Izlita Razak …[et al.]

Razak, Zura Izlita and Abdul-Rahman, Shuzlina and Mutalib, Sofianita and Abdul Hamid, Nurzeatul Hamimah (2018) Web mining in classifying youth emotions / Zura Izlita Razak …[et al.]. Malaysian Journal of Computing (MJoC), 3 (1). pp. 1-11. ISSN 2600-8238

Official URL: https://mjoc.uitm.edu.my


Social media sites are websites used as mediums to create and share various types of contents over the internet. These sites can also be accessed through applications on mobile gadgets. Different social media sites are available for free, and most teenagers or youths have at least one active account. They use social media sites to connect and share their online profiles, daily activities, stories, and emotions. Depending on their social settings, their activities may or may not be seen by others. One of the latest trends that is spreading over the social media is the Korean Pop entertainment or popularly known as KPop. Over the social media, youths share and express how they feel about their Korean celebrities, music, and drama. However, the issue of excessive sharing of emotion-sharing over social media may increase the risk of mental illness and affect their mental health. Their obsession to keep up-to-date with their idols might lead or cause adverse consequences on their emotional states of mind. Thus, the aim of this research is to study the changes of youths’ emotions in two different countries which are Malaysia and Korea that are related to the KPop trend. We extract texts from tweets from Twitter social media sites using the Twitter API as the basis of our study. Then, the keyword 'KPop' is used to filter the tweets. Web mining model classifies the 12,000 tweets into six emotion categories, which are joy, sadness, fear, anger, disgust, and surprise. The system then records the emotion changes and the triggering events respectively.


Item Type: Article
Email / ID Num.
Razak, Zura Izlita
Abdul-Rahman, Shuzlina
Mutalib, Sofianita
Abdul Hamid, Nurzeatul Hamimah
Subjects: Q Science > QA Mathematics > Online data processing
Q Science > QA Mathematics > Web databases
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Malaysian Journal of Computing (MJoC)
UiTM Journal Collections: UiTM Journal > Malaysian Journal of Computing (MJoC)
ISSN: 2600-8238
Volume: 3
Number: 1
Page Range: pp. 1-11
Keywords: Emotion analysis, KPop, Social media, Sentiment analysis, Twitter, Web mining
Date: 2018
URI: https://ir.uitm.edu.my/id/eprint/43157
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