Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model

Hejing Liu, Qiudan Li, Riheng Yao, Daniel Dajun Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019
EditorsXiaolong Zheng, Ahmed Abbasi, Michael Chau, Alan Wang, Lina Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages212-214
Number of pages3
ISBN (Electronic)9781728125046
DOIs
StatePublished - Jul 2019
Externally publishedYes
Event17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019 - Shenzhen, China
Duration: Jul 1 2019Jul 3 2019

Publication series

Name2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019

Conference

Conference17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019
CountryChina
CityShenzhen
Period7/1/197/3/19

Fingerprint

Semantics
Merging
Monitoring
Social media
Key words
Cigarettes
Surveillance

Keywords

  • E-cigarettes
  • JUUL
  • Short posts
  • Topic analysis

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Information Systems

Cite this

Liu, H., Li, Q., Yao, R., & Zeng, D. D. (2019). Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model. In X. Zheng, A. Abbasi, M. Chau, A. Wang, & L. Zhou (Eds.), 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019 (pp. 212-214). [8823541] (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISI.2019.8823541

Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model. / Liu, Hejing; Li, Qiudan; Yao, Riheng; Zeng, Daniel Dajun.

2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019. ed. / Xiaolong Zheng; Ahmed Abbasi; Michael Chau; Alan Wang; Lina Zhou. Institute of Electrical and Electronics Engineers Inc., 2019. p. 212-214 8823541 (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, H, Li, Q, Yao, R & Zeng, DD 2019, Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model. in X Zheng, A Abbasi, M Chau, A Wang & L Zhou (eds), 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019., 8823541, 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019, Institute of Electrical and Electronics Engineers Inc., pp. 212-214, 17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019, Shenzhen, China, 7/1/19. https://doi.org/10.1109/ISI.2019.8823541
Liu H, Li Q, Yao R, Zeng DD. Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model. In Zheng X, Abbasi A, Chau M, Wang A, Zhou L, editors, 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 212-214. 8823541. (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019). https://doi.org/10.1109/ISI.2019.8823541
Liu, Hejing ; Li, Qiudan ; Yao, Riheng ; Zeng, Daniel Dajun. / Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model. 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019. editor / Xiaolong Zheng ; Ahmed Abbasi ; Michael Chau ; Alan Wang ; Lina Zhou. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 212-214 (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019).
@inproceedings{e9e7e0659b1b4676859d870f58ff1191,
title = "Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model",
abstract = "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.",
keywords = "E-cigarettes, JUUL, Short posts, Topic analysis",
author = "Hejing Liu and Qiudan Li and Riheng Yao and Zeng, {Daniel Dajun}",
year = "2019",
month = "7",
doi = "10.1109/ISI.2019.8823541",
language = "English (US)",
series = "2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "212--214",
editor = "Xiaolong Zheng and Ahmed Abbasi and Michael Chau and Alan Wang and Lina Zhou",
booktitle = "2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019",

}

TY - GEN

T1 - Analyzing topics of JUUL discussions on social media using a semantics-assisted NMF model

AU - Liu, Hejing

AU - Li, Qiudan

AU - Yao, Riheng

AU - Zeng, Daniel Dajun

PY - 2019/7

Y1 - 2019/7

N2 - 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.

AB - 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.

KW - E-cigarettes

KW - JUUL

KW - Short posts

KW - Topic analysis

UR - http://www.scopus.com/inward/record.url?scp=85072964964&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85072964964&partnerID=8YFLogxK

U2 - 10.1109/ISI.2019.8823541

DO - 10.1109/ISI.2019.8823541

M3 - Conference contribution

AN - SCOPUS:85072964964

T3 - 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019

SP - 212

EP - 214

BT - 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019

A2 - Zheng, Xiaolong

A2 - Abbasi, Ahmed

A2 - Chau, Michael

A2 - Wang, Alan

A2 - Zhou, Lina

PB - Institute of Electrical and Electronics Engineers Inc.

ER -