论文标题
通过眼睛跟踪的事实检查新闻头条
Factuality Checking in News Headlines with Eye Tracking
论文作者
论文摘要
我们研究新闻头条新闻头条时仅使用人眼的运动是正确还是错误，是否有可能推断出。我们对55名参与者的研究在阅读108个新闻头条（72个True，36 False）时会引人注目，这表明虚假的头条在统计学上的视觉关注明显少于真正的头条新闻。我们进一步构建了一个合奏学习者，该学习者仅使用眼球追踪测量值来预测新闻标题的事实。我们的模型的平均AUC为0.688，并且比真实头条更擅长检测错误。通过模型分析，我们发现在阅读3-6个头条新闻时，对我们的合奏学习者来说，吸引了25位用户。
We study whether it is possible to infer if a news headline is true or false using only the movement of the human eyes when reading news headlines. Our study with 55 participants who are eye-tracked when reading 108 news headlines (72 true, 36 false) shows that false headlines receive statistically significantly less visual attention than true headlines. We further build an ensemble learner that predicts news headline factuality using only eye-tracking measurements. Our model yields a mean AUC of 0.688 and is better at detecting false than true headlines. Through a model analysis, we find that eye-tracking 25 users when reading 3-6 headlines is sufficient for our ensemble learner.
