ABSTRACT
Based on cognitive-emotional neuroscience, the effectiveness of advertisement is measured in terms of individuals' unconscious emotional responses. Using AFFDEX to record and analyze facial expressions, a combination of indicators that track both basic emotions and individual involvement is used to quantitatively determine if a spot causes high levels of ad liking in terms of attention, engagement, valence, and joy. We use as a test case a real campaign, in which a spot composed of 31 scenes (images, text, and the brand logo) is shown to subjects divided into five groups in terms of age and gender. The target group of mature women shows statistically more positive emotions and involvement than the rest of the groups, demonstrating the emotional effectiveness of the spot. Each other experimental groups show specific negative emotions as a function of their age and for certain blocks of scenes.
ABSTRACT
It is well known that excessive rescue times after traffic accidents negatively affect the health of those injured. There is a need to quantitatively measure the impact of unexpected events like ambulance availability, weather, floating population and congestion in those rescue times. A family of indicators based on isochrones is disguised and proposed to understand the risk of the whole population as the probability of not being assisted on time. Indicators of health risk for local towns are also defined. The indicators are calculated using a simulation model and visualized in web format. The framework of analysis is validated using Ávila (Spain) and the problem of the optimal deployment of ambulances as a test-bench.
