Best practices in collecting online data with Asian, Black, Latino, and White respondents: evidence from the 2016 Collaborative Multiracial Post-election Survey

Abstract

As the U.S. becomes increasingly diverse, new challenges to capturing this diversity emerge for survey researchers studying political attitudes and behavior. Sampling methods are no longer straightforward as simple random-digit-dial. Given the confluence of changing demographics and changing survey technology, we argue that researchers should carefully consider a stratified listed/density quota-sampling approach to multilingual surveys with large racial/ethnic minority samples. We examine the 2016 Collaborative Multiracial Post-election Survey, which implemented this approach with great success. Our approach resulted in collecting 10,145 completed surveys, in five languages, with large samples of Asian Americans, African-Americans, Latinos, and Whites. We conclude with a set of best practices or principles for online research of racial/ethnic minority populations that we hope will guide future social science research in this domain.