Investigating Data Collection and Reporting Practices of Human Annotations in Societally Impactful Machine Learning Applications: A Systematic Review of Top-Cited IEEE Access Papers

This systematic review investigates the practices and implications of human annotations in machine learning (ML) research. Analyzing a selection of 100 papers from the IEEE Access Journal, the study explores the data collection and reporting methods employed. The findings reveal a prevalent lack of standardization and formalization in the...