Data forms the foundation of social science research. This paper compares definitions and data collection methods of "floating population" across six large-scale social surveys in China, highlighting structural differences between survey samples and the national floating population. Using a consistent model, it demonstrates how sample structure impacts analytical outcomes. Key findings include: (1) Significant definitional differences across surveys yield varied study population; (2) Estimated floating population proportions differ by survey, with both inter-provincial and intra-county migration rates generally lower than 2015 census data; (3) Floating population samples vary widely in gender, age, education, and urban-rural distribution; and (4) Basic demographic characteristics differ significantly in both significance and direction, revealing common social patterns and sample-specific biases. The study underscores the importance of measurement in defining research population, variable measurement, and statistical outcomes. It recommends using census or 2015 census data for estimating total floating population, emphasizing common patterns across samples to reflect social realities, and standardizing floating population metrics across surveys.