Knowledge Commons of Institute of Automation,CAS
Exploring Writing Pattern with Pop Culture Ingredients for Social User Modeling | |
Chiyu Cai1,2![]() ![]() ![]() | |
2019 | |
会议名称 | The 2019 International Joint Conference on Neural Networks (IJCNN) |
会议日期 | July 14-19 |
会议地点 | Budapest, Hungary |
摘要 | Social networks have significantly altered the behavior patterns of netizens all around the world. Therefore, accurate and expressive model of social users is increasingly demanded as it pose great value in a variety of scenarios, such as e-commerce, cyber security, and entertainment to name a few. In this paper, we propose the Pop Culture Attention Writing Model (PAWM) to explore the writing patterns of social users by explicitly capturing the influence of Internet pop culture ingredients with an attention mechanism. The writing pattern representations are learned by a memory network through storing and updating historical latent patterns. We then develop the Deep Social User Model via jointly modeling basic properties of social users, temporal contents, and the learned writing patterns based on PAWM. This paper is the first trial, to the best of our knowledge, which captures Internet pop culture information and applies deep neural network to model user writing pattern. A series of experiments conducted on social bot detection and social user identification demonstrate and validate the effectiveness of the proposed models. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 自然语言处理 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23643 |
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.CNCERT/CC |
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,et al. Exploring Writing Pattern with Pop Culture Ingredients for Social User Modeling[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 | ||
Exploring Writing Pa(337KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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