期刊
出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3269206.3271709
关键词
Rumor Detection; Recurrent Neural Network; Attention Mechanism
资金
- National Natural Science Foundation of China [61571424]
- Beijing Municipal Science and Technology Project [Z181100008918006]
Microblogs have become one of the most popular communication tools for news sharing. However, due to its openness and lack of supervision, rumors could also be easily posted and propagated in microblogs, which could have serious consequences. Therefore, tools for automatic detection and verification of rumors in microblogs are very valuable. In this paper, we propose a novel hierarchical neural network combined with social information (HSA-BLSTM) for rumor detection. At first a hierarchical bi-directional long short-term memory model is built for representation learning. Then, the social contexts are incorporated into the network via attention mechanism. Test this model on two real-world datasets fromWeibo and Twitter demonstrate outstanding performance in both rumor detection and early detection scenarios.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据