FACS (Facial, Action, Coding, System). Discovering the algorithm of emotions
20 June 2019
Conscious Motivation
14 October 2019
Emotions have a crucial impact on our decisions. The studies by Kahneman and Tversky first and the more recent ones by Epstein and Damasio have helped us understand how much the classical theories on decision-making were abstract and therefore far removed from the reality experienced by each of us on a daily basis. The Nobel Prizes awarded to Daniel Kahneman in 2012 and to Richard Thaler in 2017 for behavioural economics definitively established the importance of this view. In the best-known of his books, Slow Thinking and Fast Thinking, Kahneman explains that the analytical and rational process (slow thinking) only concerns particular and limited situations, while in everyday life, the countless decisions we have to make are determined by much faster, synthetic and intuitive processes (fast thinking), based on the experiences we have gained and thus, inevitably, on the emotional experiences that accompanied those specific situations.
From personal experience, each of us can easily realise the large number of choices we make in this way every day. A situation that neuroscientist Antonio Damasio summarises with his famous phrase: “we are not thinking machines that get emotional, but emotional machines that think”. When we make decisions, we are mainly guided by our emotions and only then do we construct a rational explanation to support the choice we have made. This behaviour has been termed ‘post-hoc rationalisation’ by Professor Raj Raghunathan after a series of experiments conducted at the University of Texas at Austin.
The development of these studies has sparked off a young discipline, neuromarketing, which aims to make product communication and enhancement strategies more effective through the study of consumer behavioural reactions. The assessment of emotional involvement thus becomes a fundamentally important aspect in the development of effective neuromarketing strategies. The techniques prevalently adopted are eye-tracking, an indicator that traces the movement of the eyes while observing an image, or, when the experimental context allows it, the use of biophysiological surveys such as functional magnetic resonance imaging (fMRI) that identifies the areas of the brain that are active in relation to a specific stimulation.
Some prominent authors dealing with neuromarketing agree that it is not easy to predict developments in this discipline, which appears to be closely linked to advances in the field of neuroscience. Today, we are faced with an ever-increasing amount of data at our disposal, which are, however, not always easy to interpret. Aiming at a better understanding of emotional involvement also means being able to identify the type of emotion (surprise, happiness, fear, etc.) that is triggered by a given stimulation. In this direction, a field of application opens up that sees in Emotional Behavioural Analysis, a methodology derived from Paul Ekman’s studies that we have been pursuing for years through our initiatives, a tool of great interest. The Emotional Behavioural Analysis is a very interesting tool.
Emotional Behavioural Analysis is an interactive method that integrates a set of skills aimed at gaining an in-depth understanding of a subject’s emotional experience through evaluative analysis techniques that examine six different channels of communication. The advantages linked to a possible application of this methodology are very evident: the indications used by neuromarketing are based on elements of a prevalently quantitative nature, i.e. they measure the presence and intensity of a signal, an analysis capable of returning indications also of a qualitative nature is able to provide a broader and more precise representation of the situations under examination.
The second aspect relates to the possibility of monitoring, and subsequently modulating with greater precision, the emotional signals present within an advertisement, and thus not focusing solely on the emotional reactions of the viewer. The knowledge acquired in the field of facial expressions, for example, allows extremely precise control of the congruence of the emotional signals conveyed by the protagonists of a commercial, a result that guarantees better empathic involvement on the part of the viewer.
