Comprehensively clarifying green space research based on big data will provide experience and technical support for a more systematic and in-depth study. This paper carried out bibliometrics and graph analysis of WOS (Web of Science) literature in the recent 20 years by using CiteSpace and traditional literature analysis methods to sort out significant data types and research hotspots in green space research, summarize data analysis methods and research characteristics in green space research and explore future research directions. The results showed that: (1) Big data commonly applied in green space research can be divided into three categories and nine sub-categories. These data effectively quantify visitors’ behavior, experience, and urban space attributes. Based on the information, researchers have done green space use and management research, green space layout research, the health effects of green space research, the cultural ecosystem service of green space research, and the green space landscape preference research; (2) The application of big data effectively promotes quantitative analysis on green space, promotes interdisciplinary research, and provides more extensive practical guidance for urban green space planning and construction.