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Mining Significant Microblogs for Misinformation Identification: An Attention-Based Approach
Liu, Qiang1,2; Wu, Shu1,2; Wang, Liang1,2
Source PublicationACM Transactions on Intelligent Systems and Technology
2018-04
Volume9Issue:5Pages:50
AbstractWith 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.
KeywordMisinformation Identification Attention Model Social Media Significant Microblogs
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20942
Collection智能感知与计算研究中心
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
Recommended Citation
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.
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