重新定义点击诱饵，构建首个西班牙语点击诱饵数据集
Te Ahorré Un Click: A Revised Definition of Clickbait and Detection in Spanish News
- 以好奇心缺口为核心，明确定义点击诱饵的特征
- 创建3500条西班牙语新闻推文数据集，标注一致性达0.825
- 提供首个开源西班牙语点击诱饵检测基准，适合多语言研究者使用
我们重新审视了缺乏共识的点击诱饵定义，认为制造好奇心缺口是其核心特征，有别于耸人听闻或承诺不符的标题。因此提出新定义：点击诱饵是一种故意省略部分信息以引发读者好奇、吸引注意力并诱导点击的标题和预告技巧。我们通过细化概念边界和标注标准，最小化主观判断，构建了新的点击诱饵检测数据集生成方法。据此，我们创建并发布了首个开源西班牙语点击诱饵数据集TA1C（Te Ahorré Un Click，意为‘为你省下一次点击’），包含来自18家知名媒体的3,500条推文，经人工标注，达到0.825的Fleiss' K组间一致率。我们实现了强基线模型，在F1-score上达到0.84。
原文摘要 · Abstract (English)
We revise the definition of clickbait, which lacks current consensus, and argue that the creation of a curiosity gap is the key concept that distinguishes clickbait from other related phenomena such as sensationalism and headlines that do not deliver what they promise or diverge from the article. Therefore, we propose a new definition: clickbait is a technique for generating headlines and teasers that deliberately omit part of the information with the goal of raising the readers' curiosity, capturing their attention and enticing them to click. We introduce a new approach to clickbait detection datasets creation, by refining the concept limits and annotations criteria, minimizing the subjectivity in the decision as much as possible. Following it, we created and release TA1C (for Te Ahorré Un Click, Spanish for Saved You A Click), the first open source dataset for clickbait detection in Spanish. It consists of 3,500 tweets coming from 18 well known media sources, manually annotated and reaching a 0.825 Fleiss' K inter annotator agreement. We implement strong baselines that achieve 0.84 in F1-score.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。