Precisely understanding the value and perception of consumers has long been recognized as essential elements of every market-oriented company's core business strategy. For this reason, customers' affection, as the basis for the formation of human values and judgment, should be considered carefully to strengthen the product quality and competitiveness. However, conventional product design places more attention to functional attributes and requires survey process to collect customers' evaluations, neglecting the in-depth study of the underlying associations between design properties and consumers' emotions based on the abundant online consumer response resources. To improve the deficiency, this study was proposed to develop a product affective properties identification approach. Particularly, data mining techniques (e.g. web mining, text mining) are applied to capture online product review resources. Considering the characteristics of user/consumer responses and evaluations, ontology is utilized to assist in the semantic analysis. With the help of product knowledge hierarchy and electronic lexical database, product properties, which can evoke consumers' affect, can be identified. Furthermore, the identified product affective properties are prioritized to provide designers with important reference for future improvement on the product. To illustrate the proposed approach, a pilot study based on iPhone 7 was conducted, in which the influential affective properties have been identified, and a ranking of them has been mapped out.