SemEval Clickbait Spoiling Training Data

SemEval clickbait spoiling training data is a text dataset for the SemEval-2023 Task 5, contributed by user VSPuzzler on Hugging Face. It is intended for training models to generate spoilers for clickbait posts. The dataset was last updated on January 8, 2023.

Use Cases

• Train a model to generate a phrase_spoiler for a given clickbait post.
• Train a model to generate a passage_spoiler for a given clickbait post.
• Classify clickbait posts based on the required spoiler_type (e.g., phrase, passage).
• Evaluate model performance on the specific task of clickbait spoiling as defined by SemEval-2023.

Strengths

• Dataset is associated with the SemEval-2023 benchmark, ensuring a standard evaluation context.
• Platform tags indicate a size category of 1K<n<10K rows, suggesting a moderate training set.

Limitations

• Specific row count, column names, and data structure are unknown.
• Data is from 2023 and may not reflect current social media clickbait trends.
• Potential geographic bias as platform tags indicate a Region 'us' focus.

Provenance

Source

SemEval-2023 Task 5 (Clickbait Spoiling), contributed by VSPuzzler.

Collection Method

Presumably collected and annotated for the SemEval competition, but exact method is unspecified.

Freshness

Last updated 2023-01-08.

Geography

Platform tags suggest a US regional focus, but exact coverage is unknown.