Authors: Y Sang, J Stanton
Year: 2024
Published in: International Conference on Information, 2022 - Springer
Institution: Syracuse University
Research Area: Hate Speech Annotation, Individual Differences in Data Labeling
Discipline: Computational Social Science
This study explores disagreements among hate speech annotators and proposes a multidimensional scale to analyze individual differences, which could improve the value of minority-vote labels.
Methods: Mixed-method approach including expert interviews, concept mapping exercises, self-reporting questionnaires, and the development/testing of a multidimensional scale.
Key Findings: Individual differences (e.g., age, personality) and their relationship to annotators' label decisions in hate speech tasks.
DOI: https://doi.org/10.1007/978-3-030-96957-8_36
Citations: 46
Sample Size: 170
