Concepedia

Concept

dataset bias

Parents

507

Publications

42K

Citations

1.5K

Authors

508

Institutions

About

Dataset bias is an academic concept and research area focused on the systematic distortion or skewed representation present in a dataset, which leads to inaccurate or unfair outcomes when the data is used for analysis, modeling, or decision-making. This concept investigates the sources, characteristics, and consequences of data imperfections where the data distribution does not accurately reflect the true underlying phenomenon or target population, often resulting from sampling errors, measurement issues, or embedded societal prejudices, and is significant due to its impact on the validity, generalizability, and ethical implications of data-driven insights and systems.

Top Authors

Rankings shown are based on concept H-Index.

KR

IBM Research - Thomas J. Watson Research Center

WZ

University of Maryland, Baltimore County

JS

New York University

EF

University of Southern California

JK

Cornell University

Top Institutions

Rankings shown are based on concept H-Index.

Pittsburgh, United States

Cornell University

Ithaca, United States

Google (United States)

Mountain View, United States

University College London

London, United Kingdom

Stanford University

Stanford, United States