Table 1.
Descriptive Statistics, Description of Coding Criteria, and Selected Paraphrase Tweets for Each Theme
| Theme | Total count | Likes Md (Range) | Retweets Md (Range) | Coding criteria | Example Tweets |
|---|---|---|---|---|---|
| Political Referendum | 1913 | 1 (0–62)a | 0 (0–173)a | Mentions of removing the incumbent out of office, including governors, the president, senators, or other elected officials. Mentions of voting, including the hashtags or phrases, “we vape we vote” “I vape I vote” and “we vote we matter” | “Gov. Cuomo, I will vote for anyone that understands that vaping flavors saved my life” “POTUS will lose in 2020 if he bans flavors” |
| Institutional Distrust | 782 | 1 (0–217)b | 0 (0–141)b | Mentions of distrust of individual actors representing government, including public health organizations, and media organizations, including mentions of fake news, accusations over decreases in tax revenue from combustible tobacco sales, and references to Master Settlement Agreement | “Why did it take the CDC so long to respond to e-cigarette harm? It must be the Master Settlement Agreement blood money.” “The Surgeon General is trying to help Big Tobacco and continue receiving Master Settlement Agreement blood money.” |
| Individual Rights | 261 | 1 (0–55)c | 1 (0–28)c | Mentions of personal freedoms and liberties, restrictions on vaping are a form of oppression, flavor bans prevent people from earning a living | “Do not take away my right to vape honey nut cereal nicotine liquid” “The flavor ban will destroy the ability of thousands of small businesses to make an honest living” |
| Misinformation | 148 | 2 (0–58)d | 0 (0–31)d | Posts that include unsubstantiated health claims such as vaping is safe, harmless, health-promoting in the case of chronic diseases; posts identifies an e-cigarette or related component part and uses adjectives to describe it as safe or healthy | “Vaping is 95% safer than conventional cigarettes” “I don’t want anything FDA approved. I’ll use my 95% safer harm reducing e-liquid” |
| THC Vaping is the Real Problem | 87 | 1 (0–37)e | 0 (0–29)e | Posts that suggest black market or underground cannabis-related products are the real threat to health and not nicotine products | “e-Cigarettes are not linked to lung disease. The news said it was black market THC.” “480K death due to combustible cigarettes; 40+ deaths due to illegal black market THC; 0 deaths dues to e-cigarettes” |
| Smoking Cessation | 165 | 2 (0–116)f | 0 (0–44)f | Mentions of the use of flavored vaping products to successfully quit cigarettes | “I quit a 30-year cigarette habit with flavored e-cigarettes” “I haven’t smoked in 7 years because of vaping flavors” |
| Adult Use | 199 | 1 (0–183)g | 0 (0–63)g | Mentions that adults like flavors—this may include references to smoking cessation and draws comparisons to those under 21 | “Don’t just focus on kids; adults like flavors too” “I am an adult that used Blueberry Sugar Buzz to quit smoking” |
| Not a Bot | 276 | 1 (0–217)h | 0 (0–141)h | Mentions of not being a bot (ie, automated accounts programmed to post about specific topics on social media) in any form | “I vape, I vote. #NotABot” “I quit smoking with flavored e-cigarettes and I’m not a bot” |
Total number of coded tweets N = 2500. A tweet could be classified to more than one theme. A subset of tweets were no longer available for a post hoc analysis of Likes and Retweets, leaving the following counts for each theme: aN = 1586; bN = 614; cN = 214; dN = 131; eN = 74; fN = 144; gN = 177; hN = 218