‘Sweeter Than a Swisher’: amount and themes of little cigar and cigarillo content on Twitter

Abstract

ObjectiveDespite recent increases in little cigar and cigarillo (LCC) use—particularly among urban youth, African-Americans and Latinos—research on targeted strategies for marketing these products is sparse. Little is known about the amount or content of LCC messages users see or share on social media, a popular communication medium among youth and communities of colour.MethodsKeyword rules were used to collect tweets related to LCCs from the Twitter Firehose posted in October 2014 and March–April 2015. Tweets were coded for promotional content, brand references, co-use with marijuana and subculture references (eg, rap/hip-hop, celebrity endorsements) and were classified as commercial and ‘organic’/non-commercial using a combination of machine learning methods, keyword algorithms and human coding. Metadata associated with each tweet were used to categorise users as influencers (1000 and more followers) and regular users (under 1000 followers).ResultsKeyword filters captured over 4 372 293 LCC tweets. Analyses revealed that 17% of account users posting about LCCs were influencers and 1% of accounts were overtly commercial. Influencers were more likely to mention LCC brands and post promotional messages. Approximately 83% of LCC tweets contained references to marijuana and 29% of tweets were memes. Tweets also contained references to rap/hip-hop lyrics and urban subculture.ConclusionsTwitter is a major information-sharing and marketing platform for LCCs. Co-use of tobacco and marijuana is common and normalised on Twitter. The presence and broad reach of LCC messages on social media warrants urgent need for surveillance and serious attention from public health professionals and policymakers. Future tobacco use prevention initiatives should be adapted to ensure that they are inclusive of LCC use.

Characterizing Blunt Use Among Twitter Users: Racial/Ethnic Differences in Use Patterns and Characteristics

“…First, findings from this study suggest that the actual blunt use patterns among Twitter users is consistent with the large number of marijuana and LCC related tweets found in previous studies (Cavazos-Rehg et al, 2015; Kostygina et al, 2016). Given that discussions about marijuana use are already taking place on Twitter, findings from the current study provides ideas for messages that may be used to counter pro-marijuana and LCC tweets.…”

“…Although several studies have assessed the content of tweets that discuss marijuana and LCCs (Cavazos-Rehg et al, 2015; Kostygina et al, 2016), very few examine the actual use patterns and characteristics of Twitter users who report current blunt use. This study was designed to address this gap by examining the frequency and initiation of blunt use among African American, Hispanic and White Twitter users, as well as general beliefs about blunt use.…”

“…In addition, in an analysis of 2,590 tweets from a popular pro-marijuana Twitter page (@stillblazingtho), nearly 10% of tweets mentioned blunts (Cavazos-Rehg et al, 2014). Further, approximately 83% of tweets about little cigars and cigarillos (LCCs) mentioned the dual use of LCCs and marijuana, primarily via blunts (Kostygina et al, 2016). The large number of tweets that promote and encourage blunts reflects the prevalence of blunt smoking among young adult marijuana users in the United States.…”

Recent Advances in Using Natural Language Processing to Address Public Health Research Questions Using Social Media and ConsumerGenerated Data

“…Of the twenty-two papers discussed in this section, three are focussed on opioid abuse [35,41,42], eight on tobacco and marijuana use [6,12,13,40,43,45,46,49], one on alcohol abuse [36], and one on the street drug, mephedrone [44]. Twitter is the most popular source of data (18 papers) [6,11,12,[35][36][37][38][39][40][41][42][43][44][45][46][47][48][49], with Reddit [11][12][13], and online health communities [12,13], both represented. Supervised machine learning (8 papers -all utilising Twitter data) and unsupervised machine learning (11 papers) were both evident in the reviewed papers, with classical machine learning approaches more common than modern neural-network-based approaches (17 and 2 papers, respectively).…”

Is social media the way to empower patients to share their experiences of dental care?

“…In research social media has been used for recruiting participants and distributing surveys 7,8 and testing the effectiveness of provision of patient information using new digital formats 9 . Acquisition and analysis of existing data has been used for a range of purposes: evaluation of the usefulness 10 and harms to health 11 posed by information sharing and product marketing by social media communities; understanding public communication about specific conditions such as, cardiovascular disease 12 and mammography experience 13 , and providing opportunities for drug safety surveillance. 14,15 In dentistry, the current studies have used social media to explore patient experience of orthodontic treatment 16,17 , quality of life related to third molars 18 and bullying in relation to dentofacial features 19 using posts on Twitter.…”