Emotional Classification Method (ECW): A Methodology for Measuring Emotional Sustainability in a Work Environment Utilizing Artificial Intelligence

Abstract

Sustainable development generally includes three key dimensions: environmental, economic, and social. However, both in practice and in theory, the social dimension often receives less attention than the other two, even though it is just as important. This lack of focus can be seen in the lack of tools available to measure problems within the social dimension, such as emotional sustainability within the work environment. The objective of this research is to propose a methodology for emotional classification (ECM) using advanced systems such as artificial intelligence to serve as a tool for measuring emotional sustainability in a work environment. This methodology was applied in an institution whose objective was to accredit and comply with a Mexican standard (NOM-035) regarding stress and anxiety of labor personnel. As a result of the research, we have a method for emotional diagnosis that functions as a tool for the quantification and evaluation of emotions and thus contributes to the implementation of social sustainability. Finally, a proposal for improvements and factors to be taken into account in order to reproduce the ECW method is offered.

Keywords

• social sustainability
• artificial intelligence
• deep learning
• emotion classification
• emotional sustainability
• emotional diagnosis