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.
Their conclusions sure are “rock solid”!
Potentially. lol
sentiment analysis to classify the features … nuts and cream … cloud production … satisfied …
Well whudda ya know. Isn’t science amazing?
I wonder how much they got paid for that.
‘VG increases the flavor’ ???
Yes!! It’s amazing!
Every mixer, ever.
Interesting. Wrong, but interesting. Wonder who they’re going to present this to? Hmmm, let me guess.
What exactly, is amazing?
Please, explain it to me.
The world is awash with pseudo-science
And the purpose of their research?..heck they could have just asked us?
@SessionDrummer how did I miss this thread? I’ve been reading some of their data on ecigs. Did you see the E-liquid Flavor Wheel?
Proposed flavor wheel for classification of e-liquid flavors. The inner layer of the flavor wheel includes 13 main categories that were based on literature (first column, Table 1). The outer layer of the flavor wheel includes 90 subcategories that were extracted from the articles reviewed (third column, Table 1).
This is exactly how I picture you preparing your SFT notes for us