Analyzing Topics of JUUL Discussions on Social  Media Using a Semantics-assisted NMF model

CASIA OpenIR > 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

	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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