Street contact crime refers to violations of the law committed by offenders through directly contact with victims in the street such as pickpocketing, robbery and snatch, etc, which is one of the common crimes in China. It is assumed that street contact crime is the result of interaction among motivated offenders, potential targets and absence of capable guardians. Different types of big data are employed in previous studies as ambient population to represent the potential targets which is one of the essential elements in the routine activity theory. However, these types of big data can not be applied in a micro-scale study of street contact crime because of their limitations. This study aims to fill this gap by using a new type of big data, WeChat heat map, an internet application which shows demographic distribution and changes dynamically with high spatial-temporal resolution to study the street contact crime in XT, ZG city, based on dynamic spatio-temporal distribution of potential Targets. The spatio-temporal pattern of street contact crime in XT, ZG city and their influencing factors were revealed. Street contact crime data, Points of Interest (POI) and data of house prices in XT, ZG city were used in this study as well. The whole day is divided into three intervals (wee hours: 00:00-06:59, daytime:07:00-17:59, night:18:00-23:59) and negative binomial regression models are built for the three intervals accordingly. It is demonstrated that the spatio-temporal distribution of street contact crime in XT, ZG city aggregates obviously. Street contact crime in XT, ZG city mainly concentrate in urban village and night is the peak period while daytime is the low period. The count of street contact crime in XT, ZG city reach its maximum between 22:00 and 22:59. Factors have different impacts on street contact crime from interval to interval. During the wee hours, WeChat population,KTV and leisure Club have significant positive impact on street contact crime. In the daytime, WeChat population and gym have significant positive impact on street contact crime. At night, WeChat population, restaurants, Leisure Club, bus station and distance to the nearest security department have significant positive impact on street contact crime. Others factors such as internet café, shopping mall, house prices and length of road have no significant impact on street contact crime in the whole day. WeChat population as an ambient population represent the potential targets well in routine activity theory as it has significant positive impact on street contact crime in the whole day.