Cargando…

Mining online e-liquid reviews for opinion polarities about e-liquid features

BACKGROUND: In recent years, the emerging electronic cigarette (e-cigarette) marketplace has developed prosperously all over the world. By analyzing online e-liquid reviews, we seek to identify the features attracting users. METHODS: We collected e-liquid reviews from one of the largest online e-liq...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Zhipeng, Zeng, Daniel D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501340/
https://www.ncbi.nlm.nih.gov/pubmed/28683797
http://dx.doi.org/10.1186/s12889-017-4533-z
_version_ 1783248768672464896
author Chen, Zhipeng
Zeng, Daniel D.
author_facet Chen, Zhipeng
Zeng, Daniel D.
author_sort Chen, Zhipeng
collection PubMed
description BACKGROUND: In recent years, the emerging electronic cigarette (e-cigarette) marketplace has developed prosperously all over the world. By analyzing online e-liquid reviews, we seek to identify the features attracting users. METHODS: We collected e-liquid reviews from one of the largest online e-liquid review websites and extracted the e-liquid features by keywords. Then we used sentiment analysis to classify the features into two polarities: positive and negative. The positive sentiment ratio of a feature reflects the e-cigarette users’ preference on this feature. RESULTS: The popularity and preference of e-liquid features are not correlated. Nuts and cream are the favorite flavor categories, while fruit and cream are the most popular categories. The top mixed flavors are preferable to single flavors. Fruit and cream categories are most frequently mixed with other flavors. E-cigarette users are satisfied with cloud production, but not satisfied with the ingredients and throat hit. CONCLUSIONS: We identified the flavors that e-cigarette users were satisfied with, and we found the users liked e-cigarette cloud production. Therefore, flavors and cloud production are potential factors attracting new users.
format Online
Article
Text
id pubmed-5501340
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-55013402017-07-10 Mining online e-liquid reviews for opinion polarities about e-liquid features Chen, Zhipeng Zeng, Daniel D. BMC Public Health Research Article BACKGROUND: In recent years, the emerging electronic cigarette (e-cigarette) marketplace has developed prosperously all over the world. By analyzing online e-liquid reviews, we seek to identify the features attracting users. METHODS: We collected e-liquid reviews from one of the largest online e-liquid review websites and extracted the e-liquid features by keywords. Then we used sentiment analysis to classify the features into two polarities: positive and negative. The positive sentiment ratio of a feature reflects the e-cigarette users’ preference on this feature. RESULTS: The popularity and preference of e-liquid features are not correlated. Nuts and cream are the favorite flavor categories, while fruit and cream are the most popular categories. The top mixed flavors are preferable to single flavors. Fruit and cream categories are most frequently mixed with other flavors. E-cigarette users are satisfied with cloud production, but not satisfied with the ingredients and throat hit. CONCLUSIONS: We identified the flavors that e-cigarette users were satisfied with, and we found the users liked e-cigarette cloud production. Therefore, flavors and cloud production are potential factors attracting new users. BioMed Central 2017-07-07 /pmc/articles/PMC5501340/ /pubmed/28683797 http://dx.doi.org/10.1186/s12889-017-4533-z Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Chen, Zhipeng
Zeng, Daniel D.
Mining online e-liquid reviews for opinion polarities about e-liquid features
title Mining online e-liquid reviews for opinion polarities about e-liquid features
title_full Mining online e-liquid reviews for opinion polarities about e-liquid features
title_fullStr Mining online e-liquid reviews for opinion polarities about e-liquid features
title_full_unstemmed Mining online e-liquid reviews for opinion polarities about e-liquid features
title_short Mining online e-liquid reviews for opinion polarities about e-liquid features
title_sort mining online e-liquid reviews for opinion polarities about e-liquid features
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501340/
https://www.ncbi.nlm.nih.gov/pubmed/28683797
http://dx.doi.org/10.1186/s12889-017-4533-z
work_keys_str_mv AT chenzhipeng miningonlineeliquidreviewsforopinionpolaritiesabouteliquidfeatures
AT zengdanield miningonlineeliquidreviewsforopinionpolaritiesabouteliquidfeatures