Abstract
As we live in today’s world of technology encompassing the sophisticated use of the Internet. The political scenario of a country evolves alongside the prolific rise of new media where it becomes a battlefield for political parties to win the hearts and minds of the people through videos depicting many social reality issues such as politics, religions, social and economics relating to politics, posted through social media – the YouTube. Henceforth, this study used the Evaluation Grid Method of Laddering (EGML) to identify the specimens – political agenda videos posted on YouTube relating to Malay unity based on social reality issues in relation to politics. EGML could be explained to elicit a set of constructs that define facets within the mental model of an individual, which considers each of the user’s constructs to determine the reasons for its importance within the user’s mental model. Six participants participated in this study to determine their evaluative views of videos, allowing the participants to state as many or as a few problems/solutions pertaining to the social reality issues in relation to videos on Malaysian politics as they wish, without researcher influence. The participants were asked to watch the videos; 9 videos for session one, and 10 videos for session two, and asked to make an evaluation based on their watching experience. This study used PANAS (Positive Affect and Negative Affect Schedule) as a guideline to determine the emotion involved at the Evaluative View’s part. Finally, the study enables identification of videos from the most important to the least important (for positive affect and negative affect), and the resulting identification of 64 emotions or Kansei Words (KWs) derived from both sessions. The resulting set of KWs provides dimension, which provides access to the emotional experience viewers would feel when viewing political YouTube videos.
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Kadir, S.A., Lokman, A.M., Muhammad, M. (2018). Identification of Positive and Negative Emotion towards Political Agenda Videos Posted on YouTube. In: Lokman, A., Yamanaka, T., Lévy, P., Chen, K., Koyama, S. (eds) Proceedings of the 7th International Conference on Kansei Engineering and Emotion Research 2018. KEER 2018. Advances in Intelligent Systems and Computing, vol 739. Springer, Singapore. https://doi.org/10.1007/978-981-10-8612-0_79
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DOI: https://doi.org/10.1007/978-981-10-8612-0_79
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