Mining Significant Microblogs for Misinformation Identification: An Attention-Based Approach
文献类型：期刊论文
| 作者 | Liu, Qiang1,2 ; Wu, Shu1,2; Wang, Liang1,2
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| 刊名 | ACM Transactions on Intelligent Systems and Technology
 |
| 出版日期 | 2018-04 |
| 卷号 | 9期号:5页码:50 |
| 关键词 | Misinformation Identification Attention Model Social Media Significant Microblogs |
| 英文摘要 | With the rapid growth of social media, massive misinformation is also spreading widely on social media, such as Weibo and Twitter, and brings negative effects to human life. Nowadays, automatic misinformation identification has drawn attention from academic and industrial communities. For an event on social media usually consists of multiple microblogs, current methods are mainly constructed based on global statistical features. However, information on social media is full of noisy, which should be alleviated. Moreover, most of microblogs about an event have little contribution to the identification of misinformation, where useful information can be easily overwhelmed by useless information. Thus, it is important to mine significant microblogs for constructing a reliable misinformation identification method. In this paper, we propose an Attention-based approach for Identification of Misinformation (AIM). Based on the attention mechanism, AIM can select microblogs with largest attention values for misinformation identification. The attention mechanism in AIM contains two parts: content attention and dynamic attention. Content attention is calculated based textual features of each microblog. Dynamic attention is related to the time interval between the posting time of a microblog and the beginning of the event. To evaluate AIM, we conduct a series of experiments on the Weibo dataset and the Twitter dataset, and the experimental results show that the proposed AIM model outperforms the state-of-the-art methods. |
| WOS记录号 | WOS:000463797000002 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/20942]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Liu, Qiang,Wu, Shu,Wang, Liang. Mining Significant Microblogs for Misinformation Identification: An Attention-Based Approach[J]. ACM Transactions on Intelligent Systems and Technology,2018,9(5):50. |
| APA | Liu, Qiang,Wu, Shu,&Wang, Liang.(2018).Mining Significant Microblogs for Misinformation Identification: An Attention-Based Approach.ACM Transactions on Intelligent Systems and Technology,9(5),50. |
| MLA | Liu, Qiang,et al."Mining Significant Microblogs for Misinformation Identification: An Attention-Based Approach".ACM Transactions on Intelligent Systems and Technology 9.5(2018):50. |
入库方式： OAI收割
来源：自动化研究所
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