The basic reproductive number (R0) of an infectious disease is the expected number of secondary cases infected by the first case in an otherwise susceptible population. In this thesis, based on this fundamental concept, we propose a new method: the IIN-TN method that could calculate R0 of a network from the local structure of the network under the scenario of the SIS model. The analytical solution of this method is given in this thesis, and simulations are performed to verify the result. After the code implementation in MATLAB, the method is applied to a human contact network in reality. The results from the real-world network show that the R0 calculated by the IIN-TN method will be smaller than the value given by the traditional definition. Apart from that, we also find that the IIN-TN method is more effective for infectious diseases, which have a relatively larger infection probability of link and a higher effective infection rate.