Datasets:

Modalities:
Text
Formats:
json
Libraries:
Datasets
pandas
License:

You need to agree to share your contact information to access this dataset

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Log in or Sign Up to review the conditions and access this dataset content.

Dataset Card for QA Bias Detection Dataset

Summary

  • Description: This dataset is designed for the task of bias detection in text, particularly focusing on dimensions of ageism and sentiment analysis. It contains question-answer pairs that assess potential biases in statements.
  • Purpose: To facilitate research and development in the areas of bias detection, natural language understanding, and sentiment analysis.
  • Supported Tasks: Bias detection, sentiment analysis, natural language understanding, question answering.
  • Languages: English

Composition

  • Size of Dataset: 3,900 rows.
  • Column Names: ['text', 'dimension', 'aspect', 'biased_words', 'sentiment', 'aggregate_label', 'Bias Type', 'Question', 'Answer', one column for indexing].
  • Data Format: Each record contains a text statement, its associated dimensions and aspects of bias, biased words identified, sentiment, aggregate label for bias, bias type, and a QA pair for bias detection.

Source Data

  • Initial Data Collection and Normalization: curated

Annotations

  • Annotation process: Annotations include bias type, sentiment, and question-answer pairs evaluating the presence and type of bias in the text.
  • Who are the annotators?: Human annotation.

Personal and Sensitive Information

  • Considerations: The dataset contains text that may include sensitive topics related to bias and sentiment.

Considerations for Using the Data

  • Social Impact of Dataset: The dataset could be valuable for developing systems that detect and mitigate bias in textual data.
  • Other Known Limitations: The dataset's effectiveness is limited to the scope of its annotations and the quality of its text sources.
Downloads last month
34

Collection including newsmediabias/Bias-Question-Answering