The analyses summarized in the previous section are orientated toward answering the spatiotemporal variation of urban activity.Since the crowdsourced data are collected at the individual level,it comes with multiple features of data subjects beyond spatialand temporal information. In general, sociodemographic and perspective features may directly be included in the profile of usersand the generated content, or it is hidden in the spatiotemporal preference of their activities. These features further allow the exploration of patterns of urban activity and their underlying mechanisms.This section summarizes the application of features beyond geographic information of crowdsourced data