Integrating Statistical and Visual Analytic Methods for Bot Identification of Health-related Survey Data.

Our main contributions are: 1) a proposed framework for data quality assessment, including suspect data identification and removal; 2) the analysis of potential consequences in terms of representation bias in the dataset; and 3) recommendations for implementation of this approach in practice.