Knowledge Commons of Institute of Automation,CAS
Capturing Deep Dynamic Information for Mapping Users across Social Networks | |
Chiyu Cai1,2; Linjing Li1,3; Weiyun Chen4; Daniel Zeng1,2,3 | |
2019 | |
会议名称 | 2019 IEEE International Conference on Intelligence and Security Informatics |
会议日期 | July 1-3 |
会议地点 | Shenzhen, China |
摘要 | Nowadays, it is common that a netizen creates multiple accounts across social platforms. Mapping accounts across platforms could facilitate various applications in security. Existing methods usually focus on profile and network based features. In this paper, we concentrate on capturing dynamic information of social users and present a deep dynamic user mapping model to identify the accounts across platforms. The proposed model captures dynamic latent features from three aspects including posting pattern, writing pattern, and emotional fluctuation. We also develop a matching network that fuses dynamic and traditional features to identify accounts. To the best knowledge of ourselves, this is the first trial that applies deep neural network in mapping users with dynamic information. Experiments on real world dataset demonstrated the effectiveness of the proposed method. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 社会计算 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23707 |
专题 | 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
作者单位 | 1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Shenzhen Artificial Intelligence and Data Science Institute (Longhua) 4.Huazhong University of Science and Technology |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Chiyu Cai,Linjing Li,Weiyun Chen,et al. Capturing Deep Dynamic Information for Mapping Users across Social Networks[C],2019. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Capturing Deep Dynam(330KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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