This paper explores the application of network analysis to urban street networks, addressing several key questions such as how to handle metric distances, the choice of graph representation, and the measures to investigate. The authors propose a dual approach to representing urban street networks, first as a primal graph where intersections are nodes and streets are edges, and then as a dual graph where streets are nodes and intersections are edges. They introduce an innovative generalization model called Intersection Continuity Negotiation (ICN) to capture the continuity of streets over multiple edges. The study focuses on six urban street networks from different cities, characterized by different patterns and historical roots. The authors analyze various structural properties of these networks, including degree distribution, assortative and disassortative mixing, characteristic path length, clustering coefficient, global and local efficiency, and small-world properties. The results show that most of the considered networks exhibit scale-free degree distributions and small-world properties, with some exceptions for networks with fewer triangular loops. The study also highlights significant differences in the structural order and complexity of urban networks, even within the same territorial area, suggesting that density and sustainability in urban planning are crucial factors.This paper explores the application of network analysis to urban street networks, addressing several key questions such as how to handle metric distances, the choice of graph representation, and the measures to investigate. The authors propose a dual approach to representing urban street networks, first as a primal graph where intersections are nodes and streets are edges, and then as a dual graph where streets are nodes and intersections are edges. They introduce an innovative generalization model called Intersection Continuity Negotiation (ICN) to capture the continuity of streets over multiple edges. The study focuses on six urban street networks from different cities, characterized by different patterns and historical roots. The authors analyze various structural properties of these networks, including degree distribution, assortative and disassortative mixing, characteristic path length, clustering coefficient, global and local efficiency, and small-world properties. The results show that most of the considered networks exhibit scale-free degree distributions and small-world properties, with some exceptions for networks with fewer triangular loops. The study also highlights significant differences in the structural order and complexity of urban networks, even within the same territorial area, suggesting that density and sustainability in urban planning are crucial factors.