Context Toxicity: Annotated Data for Context Sensitivity in Toxicity Detection

A 2021 research dataset from the WOAH 2021 workshop, created by Alexandros Xenos, John Pavlopoulos, and Ion Androutsopoulos. It is hosted on Hugging Face by the 'tasksource' account and was last updated in July 2023. The dataset is designed for studying how context influences the perception of toxicity in text.

Use Cases

• Training context-sensitive toxicity classifiers based on the described research focus.
• Evaluating model robustness to contextual shifts in potentially toxic language.
• Benchmarking NLP models for the task of context sensitivity estimation mentioned in the description.
• Studying the relationship between textual context and toxicity labels.

Strengths

• Dataset is associated with a peer-reviewed publication from the WOAH 2021 workshop.
• The research focus on context sensitivity is a specific and defined problem in toxicity detection.
• Hosted on the Hugging Face platform, which suggests a standard format for accessibility.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Hugging Face (tasksource), originating from research presented at WOAH 2021.

Collection Method

Likely created through annotation for the described research on context sensitivity.

Freshness

Last updated 2023-07-02 12:58:26; freshness should be verified.