Mining social media data for opinion polarities about electronic cigarettes.
BACKGROUND: There is an ongoing debate about harm and benefit of e-cigarettes, usage of which has rapidly increased in recent years. By separating non-commercial (organic) tweets from commercial tweets, we seek to evaluate the general public's attitudes towards e-cigarettes.
METHODS: We collected tweets containing the words 'e-cig', 'e-cigarette', 'e-liquid', 'vape', 'vaping', 'vapor' and 'vaporizer' from 23 July to 14 October 2015 (n=757 167). A multilabel Naïve Bayes model was constructed to classify tweets into 5 polarities (against, support, neutral, commercial, irrelevant). We further analysed the prevalence of e-cigarette tweets, geographic variations in these tweets and the impact of socioeconomic factors on the public attitudes towards e-cigarettes.
RESULTS: Opinions from organic tweets about e-cigarettes were mixed (against 17.7%, support 10.8% and neutral 19.4%). The organic-against tweets delivered strong educational information about the risks of e-cigarette use and advocated for the general public, especially youth, to stop vaping. However, the organic-against tweets were outnumbered by commercial tweets and organic-support tweets by a ratio of over 1 to 3. Higher prevalence of organic tweets was associated with states with higher education rates (r=0.60, p
CONCLUSIONS: The organic-against tweets raised public awareness of potential health risks and could aid in preventing non-smokers, adolescents and young adults from using e-cigarettes. Opinion polarities about e-cigarettes from social networks could be highly influential to the general public, especially youth. Further educational campaigns should include measuring their effectiveness.
Adolescent; Adult; Bayes Theorem; Data Mining; Electronic Nicotine Delivery Systems; Female; Humans; Male; Public Opinion; Smoking Prevention; Social Media; Socioeconomic Factors; Vaping; Young Adult
Social Media; Social marketing; Socioeconomic status; Vaping; E-cigarettes
Dai, H., Hao, J. Mining social media data for opinion polarities about electronic cigarettes. Tobacco control 26, 175-180 (2017).