Over the recent years the interest in the study of social systems by means of techniques drawn from the areas of control theory and machine learning domain has risen significantly. In particular, the analysis of social influence and opinion dynamics is one of the most representative in this field of study. Inspired by an existing and solid research active on the U.S. Congress, this thesis aims to apply these techniques to the voting data of the XVII legislature of the Italian Senate. This has been proven challenging for the higher number of both political members and parties involved in the Italian case.