论文标题
一种情感引导的方法，用于使用对抗性学习的自适应假新闻检测
An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning
论文作者
论文摘要
关于假新闻检测的最新作品表明，将情感用作提高性能的功能的功效。但是，情绪引导特征对虚假新闻检测的跨域影响仍然是一个开放的问题。在这项工作中，我们提出了一种情感引导的，域名自适应的多任务方法，用于跨域假新闻检测，证明了情感引导模型在跨域设置中的功效对各种数据集的功效。
Recent works on fake news detection have shown the efficacy of using emotions as a feature for improved performance. However, the cross-domain impact of emotion-guided features for fake news detection still remains an open problem. In this work, we propose an emotion-guided, domain-adaptive, multi-task approach for cross-domain fake news detection, proving the efficacy of emotion-guided models in cross-domain settings for various datasets.
