Understanding Users’ Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques

Abstract

BackgroundE-liquid is one of the main components in electronic nicotine delivery systems (ENDS). ENDS review comments could serve as an early warning on use patterns and even function to serve as an indicator of problems or adverse events pertaining to the use of specific e-liquids—much like types of responses tracked by the Food and Drug Administration (FDA) regarding medications.ObjectiveThis study aimed to understand users’ “vaping” experience using sentiment opinion summarization techniques, which can help characterize how consumers think about specific e-liquids and their characteristics (eg, flavor, throat hit, and vapor production).MethodsWe collected e-liquid reviews on JuiceDB from June 27, 2013 to December 31, 2017 using its public application programming interface. The dataset contains 27,070 reviews for 8058 e-liquid products. Each review is accompanied by an overall rating and a set of 4 aspect ratings of an e-liquid, each on a scale of 1-5: flavor accuracy, throat hit, value, and cloud production. An iterative dichotomiser 3 (ID3)-based influential aspect analysis model was adopted to learn the key elements that impact e-liquid use. Then, fine-grained sentiment analysis was employed to mine opinions on various aspects of vaping experience related to e-liquids.ResultsWe found that flavor accuracy and value were the two most important aspects that affected users’ sentiments toward e-liquids. Of reviews in JuiceDB, 67.83% (18,362/27,070) were positive, while 12.67% (3430/27,070) were negative. This indicates that users generally hold positive attitudes toward e-liquids. Among the 9 flavors, fruity and sweet were the two most popular. Great and sweet tastes, reasonable value, and strong throat hit made users satisfied with fruity and sweet flavors, whereas “strange” tastes made users dislike those flavors. Meanwhile, users complained about some e-liquids’ steep or expensive prices, bad quality, and harsh throat hit. There were 2342 fruity e-liquids and 2049 sweet e-liquids. There were 55.81% (1307/2342) and 59.83% (1226/2049) positive sentiments and 13.62% (319/2342) and 12.88% (264/2049) negative sentiments toward fruity e-liquids and sweet e-liquids, respectively. Great flavors and good vapors contributed to positive reviews of fruity and sweet products. However, bad tastes such as “sour” or “bitter” resulted in negative reviews. These findings can help businesses and policy makers to further improve product quality and formulate effective policy.ConclusionsThis study provides an effective mechanism for analyzing users’ ENDS vaping experience based on sentiment opinion summarization techniques. Sentiment opinions on aspect and products can be found using our method, which is of great importance to monitor e-liquid products and improve work efficiency.

User Perceptions of Different Electronic Cigarette Flavors on Social Media: Observational Study

“…There have been few studies on flavor sentiment analysis on social media [ 16 , 26 ]. One study focused on e-cigarette–related Twitter post sentiments among users with respect to different genders and age ranges [ 16 ].…”

“…However, flavor-related sentiments were not discussed. Another study showed the sentiments on e-liquid flavors mentioned on JuiceDB, but only focusing on the 2 most popular flavors, fruit and sweet flavors [ 26 ]. Our results were similar to the sentiment analysis from JuiceDB, showing that the overall sentiments for those 2 flavors were positive.…”

A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study

“…Thus, the association of user-reported health risks with e-cigarette flavorings could be explored from social media posts. A recent review on e-liquid flavors using the JuiceDB data from 2013 to 2017 found that Fruity and Sweet were the two most popular e-liquid flavors and have more positive sentiments from users [ 14 ]. However, possible associations of e-liquid flavors with health risks have not been well investigated using social media data.…”

Analysis of a Vaping-Associated Lung Injury Outbreak through Participatory Surveillance and Archival Internet Data

“…Vaping has been studied through the lens of Internet data. Social media data was the source of several studies, including Twitter [20,21], JuiceDB (a social media platform for people who vape) [22], YouTube [23], Reddit [24], and mobile apps [25]. The health effects of vaping were examined in Reddit data by Chen et al [26] and in JuiceDB by Li et al [22].…”