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Affective Design of a Tailor Made Product Led by Insights from Big Data

Authors
Li, YanLiang, PeiWang, PeiguoShi, DanqingCheng, Kai
Issue Date
2020
Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
Keywords
Affective design; Semantic; Cluster analysis; Big data; Product design
Citation
ADVANCES IN AFFECTIVE AND PLEASURABLE DESIGN, v.952, pp 280 - 286
Pages
7
Journal Title
ADVANCES IN AFFECTIVE AND PLEASURABLE DESIGN
Volume
952
Start Page
280
End Page
286
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/63479
DOI
10.1007/978-3-030-20441-9_30
ISSN
2194-5357
2194-5365
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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