The concept of residential area public service network is proposed.Four indicators,including the shortest path,the fastest path,the second-rate shortest path and the second-rate fast path that between the residential area and public service nodes,are considered to evaluate the correlation between accessibility of public service nodes and residential area housing price by Pearson product-moment correlation coefficient,and the computation model is built finally.Accordingly the influential factors of residential area housing prices are identified.As an example,the Wuhan residential area public service network is analyzed.The results show that this method can effectively identify the factors that have important effects on residential area housing prices and provide decision supports for the residential area planning and public service optimization allocation.