Saved You A Click: Automatically Answering Clickbait Titles
December 15, 2022 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Oliver Johnson, Beicheng Lou, Janet Zhong, Andrey Kurenkov
arXiv ID
2212.08196
Category
cs.CL: Computation & Language
Citations
8
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Often clickbait articles have a title that is phrased as a question or vague teaser that entices the user to click on the link and read the article to find the explanation. We developed a system that will automatically find the answer or explanation of the clickbait hook from the website text so that the user does not need to read through the text themselves. We fine-tune an extractive question and answering model (RoBERTa) and an abstractive one (T5), using data scraped from the 'StopClickbait' Facebook pages and Reddit's 'SavedYouAClick' subforum. We find that both extractive and abstractive models improve significantly after finetuning. We find that the extractive model performs slightly better according to ROUGE scores, while the abstractive one has a slight edge in terms of BERTscores.
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