Towards a framework for customer emotion detection

Abstract

Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology neuroscience, linguistics, computer science and related disciplines. Nowadays, emotional factors are important as classic functional aspects of customer purchasing behavior. Recent studies have shown that most of our purchasing choices and decisions are the result of a careful analysis of the product advantages and disadvantages and of affective and emotional aspects. Psychological literature recognizes that the emotional conditions are always present and influence every stage of decision-making in purchasing process. The main contribution of this paper is the design of a novel framework that provides the essential for customer sentiments analysis and emotion measuring in marketing. We focus our study on automatic facial expression analysis as a tool for measuring emotional customer that can predict their behavior in the decision-making.