Xiao-Li discusses the inherent trade-offs between data quality and quantity, highlighting how large datasets from social media often suffer from bias. He emphasizes the challenges of cleaning messy data and the risks of relying on overly sanitized datasets that may lead to misleading conclusions. The conversation also touches on the pitfalls of complete case analysis, which can result in unrepresentative samples and skewed insights.
