Using Onicescu's Informational Energy to Approximate Social Entropy

The informatics revolution and the major transformations induced by this to the technology, economics, politics, culture, and social systems led to a significant increase in complexity and dynamics of systems. The complexity theory has captured the attention of both, scientists and the general public, through its discussions on emergency, migration behaviour, self-organization, computer simulations and more other, in the globalization context. In that context the sciences itself become extremely complex and they faced to the adaptations of their old theories and analysis tools or in finding new ones to measure, analysis, and understand those systems. The social systems become more complex and unpredictable and necessitate the use of social psychology to better understand and monitor them. This paper introduces the usage of Onicescu's Informational Energy theory and measures, based on frequencies used in statistics, to approximate the social entropy that is based on probabilities harder to be obtained.