Knowledge Commons of Institute of Automation,CAS
Detecting Social Bots by Jointly Modeling Deep Behavior and Content Information | |
Chiyu Cai1,2; Linjing Li1; Daniel Zeng1,3 | |
2017-11 | |
会议名称 | International Conference on Information and Knowledge Management (CIKM 2017) |
会议日期 | November 6-10 |
会议地点 | Singapore |
摘要 | Bots are regarded as the most common kind of malwares in the era of Web 2.0. In recent years, Internet has been populated by hundreds of millions of bots, especially on social media. Thus, the demand on effective and efficient bot detection algorithms is more urgent than ever. Existing works have partly satisfied this requirement by way of laborious feature engineering. In this paper, we propose a deep bot detection model aiming to learn an effective representation of social user and then detect social bots by jointly modeling social behavior and content information. The proposed model learns the representation of social behavior by encoding both endogenous and exogenous factors which affect user behavior. As to the representation of content, we regard the user content as temporal text data instead of just plain text as be treated in other existing works to extract semantic information and latent temporal patterns. To the best of our knowledge, this is the first trial that applies deep learning in modeling social users and accomplishing social bot detection. Experiments on real world dataset collected from Twitter demonstrate the effectiveness of the proposed model. |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/19858 |
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.University of Arizona |
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,Daniel Zeng. Detecting Social Bots by Jointly Modeling Deep Behavior and Content Information[C],2017. |
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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 | ||
Detecting Social Bot(662KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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