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Webis Clickbait Spoiling Corpus 2022

Authors: Matthias Hagen; Maik Fröbe; Artur Jurk; Martin Potthast;

Webis Clickbait Spoiling Corpus 2022

Abstract

Webis Clickbait Spoiling Corpus 2022 The Webis Clickbait Spoiling Corpus 2022 (Webis-Clickbait-22) contains 5,000 spoiled clickbait posts crawled from Facebook, Reddit, and Twitter. This corpus supports the task of clickbait spoiling, which deals with generating a short text that satisfies the curiosity induced by a clickbait post. This dataset contains the clickbait posts and manually cleaned versions of the linked documents, and extracted spoilers for each clickbait post. Additionally, the spoilers are categorized into three types: short phrase spoilers, longer passage spoilers, and multiple non-consecutive pieces of text. This dataset contains the clickbait posts and manually cleaned versions of the linked documents, and extracted spoilers for each clickbait post. Additionally, the spoilers are categorized into three types: short phrase spoilers, longer passage spoilers, and multiple non-consecutive pieces of text. The test set of this dataset was used for the SemEval-2023 clickbait spoiling task. You can re-execute and adopt the software submissions made through for this SemEval task, please see the instructions and overview of approaches in TIRA. Overview The dataset comes with predefined train/validation/test splits: training.jsonl: 3,200 posts for training validation.jsonl: 800 posts for validation test.jsonl: 1,000 posts for testing The test set was used for the SemEval-2023 clickbait spoiling task. This shared task was organized with TIRA.io and participants submitted Docker software during the task. Please see the instructions in TIRA to re-execute or modify the approaches.

Keywords

clickbait, clickbait spoiling, question answering

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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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