Current governmental data on rental housing-only by agencies have to be registered- do not reflect real market activity on the Taipei rental market. This study is trying to use web scraping to collect the big data. By cleaning, analyzing and mapping the data reveal spatial and temporal patterns cross districts housing markets in Taipei City. 

The rental market issue is more important in Taipei with surging housing price. The research will build the rent model to estimate fair rent of different types housing. To assess the rent affordability by the ratio between social housing rent and fair rent. To calculate the rent burdens by the ratio between median household income and median rent across the statistical area. We use two indicators that rent affordability and rent burden to discuss the social housing policy in Taipei. The findings are to capture the real rental market in Taipei and to provide suggestions for social housing policy by using big data.