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The increasing complexity of modern society requires to put a special focus on formal organizations, as places of concentration of social relations that affect most of our existence.

Several techniques have been developed to address the social and organizational complexity through models that attempt to highlight the structure of the system, as decision support systems.
The method most commonly used to understand staff social networks within organizations is Social Network Analysis, a sociological theory that integrates constructs from math and statistics in order to analyze the structure of informal relationships inside organizations.
Human Resource consultancies that use this technique generally administer questionnaires and collect data in matrix form, leading to a graphical analysis summary in the form of networks.

The software normally assigned to the visualization of graphs, however, results in fragmented and isolated static graphs that rarely convey the complexity and dynamism of the system, and are often uncommunicative and are seldom user-friendly.
Understanding that an organization is a complex system, made up of networks of communications, the thesis explores the primary organizational and decision-making theories, and the models and features of network visualization patterns.
The final project suggest the utility of an alternative and diverse way of visualizing the results of such an analysis. The model would be more flexible, focused organizational needs; interactive and with different display patterns which reveal different aspects of the data.

The thesis project suggests the need of a system able to restore the complex and multidimensional structure of relationships, which could be used in both the diagnostic and decision-making phases and would better manage the flow of communications within an organization.