Computational visualization of customer mood using affective space model approach

Kamaruddin, Norhaslinda and Handayani, Dini Oktarina Dwi and Abdul Rahman, Abdul Wahab (2017) Computational visualization of customer mood using affective space model approach. In: 16th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, SoMeT 2017, 26th-28th September 2017, Kitakyushu, Japan.

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Abstract

Customers' mood information is acquired to facilitate marketers' understanding in order to tailor the marketing strategies for positive outcomes optimization. Mood can be reasonably hypothesized as one of the factor that influences customers' decision in buying the products or services offered. There have been many researchers reporting the correlation between moods and buying decision. However, to date, there is no such method that can exactlyquantify the customer's mood. Typically, a questionnaire is given to the participant to gauge their mood on the focused product or services. The drawback from such approach is that participants can fake, exaggerate or suppress their mood resulting to questionable inference. Hence, a new method of data acquisition is needed to be able to visualize the dynamics of the customers' mood for more accurate analysis. In this paper, the customer brain signal is captured using electroencephalogram (EEG) to track and record brain wave patterns in regard to their emotional states. The sequence of emotion is then used to identify their mood. A computational visualization technique is adopted to facilitate understanding of one minute emotion transition that assembling mood. The experimental results show that such approach is feasible and can be extended to study mood in a more comprehensive manner. It is envisaged that this work will be the catalyst for large mood data analysis tool that can help researchers in the near future to look at mood and buying decision for the improvement of comprehensive customer understanding in a more accurate manner.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	6145/63005
Uncontrolled Keywords:	Affective Space Model, Buying decision, Electroencephalogram (EEG), Mood, Valence arousal approach
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Prof Abdul Wahab Abdul Rahman
Date Deposited:	23 Mar 2018 15:52
Last Modified:	27 Jul 2018 15:48
URI:	http://irep.iium.edu.my/id/eprint/63005

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