In addition to the functionality, prices, performance and quality of new products, consumers are increasingly concerned with affective aspects such as texture, outlook, colour, forms and images of newproducts. Nowadays, affective aspects of products without doubt play an important role in contributing to their success in themarket place. As an early example, the concept of affective design was originated from Kurosu and Kashimura who developed two cash teller machines having identical functional features (Kurosu and Kashimura 1995). One machine was equipped with attractive buttons and screen, and the other was with less attractive ones. User surveys indicated that the most attractive one could help promote apparent usability (Norman 2002; Zhang and Li 2005). Using amore recent example of affective design of smartphones, surveys have shown that smartphones that were equipped with more attractive interface designs helped promote the product, although smartphones are generally developedwith similar functions (Kim and Lee 2016). These two studies indicate that products with good affective design excite psychological feelings and improve consumer satisfaction in terms of emotional aspects. Therefore, considering affective aspects in engineered product designs is essential to identify and develop pleasurable features into new products that meet affective needs of customers. Affective needs of customers are commonly collected by surveys. Potential consumers are asked to fill in questionnaires and/or participate in interviews in order to uncover their affective needs towards products. However, conducting surveys/interviews is generally expensive and time consuming and there is no guarantee that all domains of affective needs can be captured. Since only limited Kansei words and affective needs can often be addressed in surveysor interviews, important affectiveneeds for newproductdevelopment may be partially or fully overlooked. Thanks to the advanced technologies of capturing ‘big data’, 2.5 quintillion bytes of data can be captured on a daily basis through the internet such as pervasive sensor networks, social media, web pages, or blogs (IBM 2015). ‘Big data’ can be used to capture useful information for developing corporate strategies, marketing campaigns and new products. Many companies adopt affective computing to realise product differentiation strategies. Techniques involving big data can potentially be applied to affective design. In line with the technologies of big data, affective computing has been examined over the past few years including product design (Ayas 2011; Koutsabasis and Istikopoulou 2013), fashion design (Sokolova and Fernández-Caballero 2015), web design (Koutsabasis and Istikopoulou 2013), media communication (Bergen and Ross 2013; Cao et al. 2014), computer game (Yannakakis et al. 2014), human computer interaction (Bakhtiyari, Taghavi, and Husain 2015; Park and Zhang 2015), service development (Hensher 2014; Morris and Guerra 2015) and urban landscape design. From the literature, a growing interest in mining multi-disciplinary affective data by both researchers and industry can be seen.

中文翻译：

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大数据情感设计专刊

除了新产品的功能、价格、性能和质量，消费者越来越关注新产品的质地、外观、颜色、形式和图像等情感方面。如今，产品的情感方面无疑在促进其在市场上的成功方面发挥着重要作用。作为一个早期的例子，情感设计的概念起源于 Kurosu 和 Kashimura，他们开发了两种具有相同功能特征的自动取款机（Kurosu 和 Kashimura，1995）。一台机器配备了吸引人的按钮和屏幕，另一台机器配备了不太吸引人的按钮和屏幕。用户调查表明，最具吸引力的可以帮助提升明显的可用性（Norman 2002；Zhang 和 Li 2005）。使用最近的智能手机情感设计示例，调查表明，配备更有吸引力的界面设计的智能手机有助于推广产品，尽管智能手机通常具有相似的功能（Kim 和 Lee 2016）。这两项研究表明，具有良好情感设计的产品会激发心理感受，提高消费者在情感方面的满意度。因此，在工程产品设计中考虑情感方面对于识别令人愉悦的功能并将其开发到满足客户情感需求的新产品中至关重要。顾客的情感需求通常通过调查来收集。潜在消费者被要求填写问卷和/或参与访谈，以揭示他们对产品的情感需求。然而，进行调查/访谈通常既昂贵又费时，并且不能保证能够捕捉到所有情感需求领域。由于在调查或访谈中通常只能解决有限的感性词汇和情感需求，因此可能会部分或完全忽略新产品开发的重要情感需求。得益于捕获“大数据”的先进技术，每天可以通过互联网捕获 2.5 千亿字节的数据，例如无处不在的传感器网络、社交媒体、网页或博客 (IBM 2015)。“大数据”可用于获取有用的信息，用于制定企业战略、营销活动和新产品。许多公司采用情感计算来实现产品差异化战略。涉及大数据的技术可以潜在地应用于情感设计。与大数据技术相一致，情感计算在过去几年中得到了检验，包括产品设计（Ayas 2011；Koutsabasis 和 Istikopoulou 2013）、时装设计（Sokolova 和 Fernández-Caballero 2015）、网页设计（Koutsabasis 和 Istikopoulou 2013） )、媒体传播（Bergen 和 Ross 2013；Cao 等人 2014）、电脑游戏（Yannakakis 等人 2014）、人机交互（Bakhtiyari、Taghavi 和 Husain 2015；Park 和 Zhang 2015）、服务开发（Hensher 2014） ；Morris 和 Guerra 2015）和城市景观设计。从文献中可以看出，研究人员和行业对挖掘多学科情感数据越来越感兴趣。Koutsabasis 和 Istikopoulou 2013）、时装设计（Sokolova 和 Fernández-Caballero 2015）、网页设计（Koutsabasis 和 Istikopoulou 2013）、媒体传播（Bergen 和 Ross 2013；Cao 等人 2014）、电脑游戏 (Yanna.) 、人机交互（Bakhtiyari、Taghavi 和 Husain 2015；Park 和 Zhang 2015）、服务开发（Hensher 2014；Morris 和 Guerra 2015）和城市景观设计。从文献中可以看出，研究人员和行业对挖掘多学科情感数据越来越感兴趣。Koutsabasis 和 Istikopoulou 2013）、时装设计（Sokolova 和 Fernández-Caballero 2015）、网页设计（Koutsabasis 和 Istikopoulou 2013）、媒体传播（Bergen 和 Ross 2013；Cao 等人 2014）、电脑游戏（Yanna） 、人机交互（Bakhtiyari、Taghavi 和 Husain 2015；Park 和 Zhang 2015）、服务开发（Hensher 2014；Morris 和 Guerra 2015）和城市景观设计。从文献中可以看出，研究人员和行业对挖掘多学科情感数据越来越感兴趣。服务开发（Hensher 2014；Morris 和 Guerra 2015）和城市景观设计。从文献中可以看出，研究人员和行业对挖掘多学科情感数据越来越感兴趣。服务开发（Hensher 2014；Morris 和 Guerra 2015）和城市景观设计。从文献中可以看出，研究人员和行业对挖掘多学科情感数据越来越感兴趣。