Abstract
How to explore precisely the affective demand of customers is an important area of research for the designers. Here we address this challenge by collecting the online comments of customers as big data, and applying the Software Kismet Affective Engine to perform the semantic cluster analysis of the big data. The design elements of a tailor made product is analyzed and associated with the affective elements of the customers. The key words of design elements and effective elements would be used to build the frame of the affective design data bank. The methods and results of this study could be very important and helpful for the market consultancy and can be extended in many other design areas as well. Especially, the affective elements with high positive valence would be extremely important to enlighten and educate the designers.
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Acknowledgments
This study was supported by the Fund of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province (project reference no.: 2017SJB1396 and 2018SJA1375).
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Li, Y., Liang, P., Wang, P., Shi, D., Cheng, K. (2020). Affective Design of a Tailor Made Product Led by Insights from Big Data. In: Fukuda, S. (eds) Advances in Affective and Pleasurable Design. AHFE 2019. Advances in Intelligent Systems and Computing, vol 952. Springer, Cham. https://doi.org/10.1007/978-3-030-20441-9_30
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DOI: https://doi.org/10.1007/978-3-030-20441-9_30
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