BiasScan
Collection
A dataset for news media biases with multiple tasks. • 13 items • Updated • 7
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.
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