GRU

2019, ACL data: TWITTER, WEIBO links: https://www.aclweb.org/anthology/N19-1163, https://github.com/DeepBrainAI/ERD task: Rumour Detection 这篇文章采用GRU编码社交媒体posts stream，作为环境的状态表示；训练一个分类器以GRU的状态输出为输入，对文本做二分类判断是否是rumor。用DQN训练agent，根据状态做出是否启动rumor分类器进行判断，并根据分类结果对错给予奖惩。目标就是尽可能准尽可能早地预测出社交媒体posts是否是rumor。 Focuses on the task of rumour detection; particularly, we are in- terested in understanding how early we can detect them. Our model treats social media posts (e.g. tweets) as a data stream and integrates reinforcement learning to learn the number minimum num- ber of posts required before we classify an event as a rumour. Let $E$ denote an event, and it consists of a series of relevant posts $x_i$, where $x_0$ denotes the source message and $x_T$ the last relevant message....