Knowledge Commons of Institute of Automation,CAS
Analyzing Topics of JUUL Discussions on Social Media Using a Semantics-assisted NMF model | |
Hejing Liu1,2,3; Qiudan Li1,3; Riheng Yao1,2,3; Daniel Dajun Zeng1,2,3 | |
2019 | |
会议名称 | 2019 IEEE International Conference on Intelligence and Security Informatics (ISI) |
会议日期 | 2019-7-1 |
会议地点 | Shenzhen, China |
摘要 | JUUL has become a widely used brand of e-cigarettes which takes more than 70% of the market. Social media provides a popular platform for users to discuss the preference and perceptions of JUUL. The discussions are valuable for real-time monitoring of JUUL use. Current research on topic analysis of JUUL discussions mainly relies on human work, which takes much time and effort. This paper adopts a Semantics-assisted NMF topic analysis model to automatically discover topics from JUUL-related short posts on Reddit. By successfully merging the semantic relationships into traditional NMF, this model outperforms in discovering topics with keywords that are important but have a lower word frequency among the posts. Experimental results show the potential of this model in JUUL surveillance and control practice. |
收录类别 | EI |
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/173211/44314 |
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 |
通讯作者 | Qiudan Li |
作者单位 | 1.The State Key Laboratory of Management and Control for Complex Systems , Institute of Automation, Chinese Academy of Sciences Beijing 100190, China 2.University of Chinese Academy of Sciences, Beijing, China 3.Shenzhen Artificial Intelligence and Data Science Institute (Longhua) |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Hejing Liu,Qiudan Li,Riheng Yao,et al. Analyzing Topics of JUUL Discussions on Social Media Using a Semantics-assisted NMF model[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 | ||
Analyzing Topics of (248KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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