When Does Demographic Information Help? Data and Modeling Regimes for Perspective-Aware Hate Speech Detection
Weibin Cai, Reza Zafarani
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Key claim
Demographics improve model performance in specific data regimes.
This paper investigates the role of demographic information in hate speech detection, revealing that its effectiveness varies based on data characteristics and modeling approaches. The key finding is that demographic gains are most pronounced in scenarios with low training disagreement and high test disagreement, leading to the introduction of a new model that selectively incorporates demographic data.
In plain English
This paper investigates the role of demographic information in hate speech detection, revealing that its effectiveness varies based on data characteristics and modeling approaches. The key finding is that demographic gains are most pronounced in scenarios with low training disagreement and high test disagreement, leading to the introduction of a new model that selectively incorporates demographic data.
The paper introduces a gated demographic residual model, extending the understanding of demographic features in model performance.
The experiments are conducted on multiple datasets with clear evaluation metrics, supporting the claims made.
Deep reliability assessment
The methodology supports the claim that demographic information can be beneficial under specific data regimes and modeling frameworks, but it may overclaim the generalizability of these findings across different datasets and domains.
Reproducibility
No open source code or dataset URL is mentioned in the paper.
Discussion questions
- 1.How do the identified regimes for demographic gains hold up across different languages and cultural contexts?
- 2.What are the practical implications for integrating demographic information in real-world hate speech detection systems?
- 3.What evidence would contradict the claim that demographic information is only useful under specific data and modeling conditions?
Key figure
Figure 1 illustrates how data split and modeling frameworks jointly determine the effectiveness of demographic information in improving model performance.