Abstract:

 

Recently, the investigation of consumer emotional experiences has been an area of active research. Understanding these experiences can provide insights that go beyond those provided by traditional liking ratings and preference responses. One challenge that can stand between researchers and the use of this new type of data is the choice of a lexicon of terms that will provide good coverage of the consumer emotion space while avoiding redundant information.

 

In this report, we describe a two-step approach to producing such lexicons. In the first step, we will map consumers’ emotional responses using Landscape Segmentation Analysis® (LSA). LSA provides a visual but quantitative tool to study similarity between the emotions and the consumer responses. Once an LSA map has been generated, the second step is to use tools from the field of Graph Theory to find lexicons of emotions that span the emotion space with minimal redundancy. Practical considerations can then inform the choice of final lexicon, and this lexicon can then be used in future research to study emotional responses in as efficient a manner as possible.