论文标题
为您节省了单击：自动回答点击诱饵标题
Saved You A Click: Automatically Answering Clickbait Titles
论文作者
论文摘要
通常，点击诱饵文章的标题被用作问题或模糊的预告片，它可以吸引用户单击链接并阅读文章以找到解释。我们开发了一个系统，该系统将自动从网站文本中找到ClickBait Hook的答案或说明，以便用户无需阅读文本本身。我们使用从“ StopClickBait” Facebook页面和Reddit的“ SavedyOuaclick”子Forum的数据中删除的数据微调了一种提取性问答模型（Roberta）和抽象性模型（T5）（T5）。我们发现，鉴定后，提取模型和抽象模型均显着改善。我们发现，根据胭脂分数，提取模型的性能稍好一些，而抽象的模型在Bertscores方面具有略有优势。
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.
