This low representation of smoking-related twitter topics likely was impacted by the methodology of data collection and its associated limitations . Of the 34 smoking-related keywords used to query the Twitter API, eight returned over 100 tweets from college campuses during this time period: cigarette , dip , joint , njoy , pipe , smoke , smoking , and weed . Upon further examination, it was determined that “njoy” returned tweets with the word “enjoy” in 99.2% of cases, and “dip” also predominantly returned false positives. After excluding these two terms, longitudinal analysis revealed that the rate of “weed” in the corpus decreased through the study time period, with it being found in 28% of tweets in 2015, 15% in 2016, 10% in 2017, 14% in 2018, and 7% in 2019. Conversely, the rate of “pipe” in the corpus increased from 7% in 2015 to 14% in 2016, 16% in 2017, 14% in 2018, and 12% in 2019. Also notable was the rate of “joint,” which increased from 6% in 2015 to 15% in 2016, 19% in 2017, 16% in 2018, and 14% in 2019. The frequency of these keywords may have been impacted by changes in the way users communicate about smoking-related topics, in addition to the potential impact of legalization of adult-use cannabis in 2016. Other terms were comparatively stable, with “smoke” returning the top number of tweets in the corpus for any given year in the study period. From this subset of filtered geocoded data, manual review identified 1,089 “signal” tweets relating directly to smoking topics, vertical grow system with 509 relating to tobacco, 490 relating to marijuana, 79 relating to vaping, and 7 relating to multiple product types in the same tweet .
Sixty eight CA colleges were represented in our signal data, though the top 20 accounted for 783 of tweets. Individual colleges exhibited high variation in the proportion of tweets corresponding to each smoking product assessed . Out of the top twenty colleges by tweet volume, the distribution of tobacco-related tweets ranged from 26.1% for CSU Long Beach to 62.2% for CSU San Jose [median [M] = 43.1%, standard deviation [SD] = 10.7%]. Vaping-related tweets were detected from eighteen of these twenty colleges, ranging from 1.6% for CSU Northridge to 21.1% for CSU Fullerton . Finally, the distribution of marijuana related tweets ranged from 28.6% for CSU San Marcos to 61.9% for the University of Southern California .Positive sentiment about tobacco, marijuana, and vaping was detected from 736 tweets. Out of the top twenty colleges by tweet volume, positive sentiment ranged from 55.0% for CSU Long Beach to 95.8% for CSU Los Angeles . When computed as a proportion of all tweets with smoking-related behavior, including neutral tweets without clear user sentiment, positive sentiment ranged from 47.4% for both CSU Fullerton to 80.9% for CSU Santa Barbara . With the exception of CSU Long Beach and CSU Fullerton , all colleges had at least 50% positive sentiment from tweets about smoking . Across product categories, positive sentiment varied with 58.2% for vaping, 66.1% for tobacco, and 70.7% for marijuana.
When calculated as a proportion of all tweets, positive sentiment was 63.9% for vaping, 70.6% for tobacco, and 85.5% for marijuana. The majority of tweets from any product category exhibited either positive or negative sentiment, with only 8.9% of tweets about vaping, 6.3% about tobacco, and 17.3% about marijuana having neutral sentiment. Therefore, while the majority of tweets about any product exhibited either positive or negative sentiment, the data suggests that tweets about tobacco or vaping were much more opinionated than marijuana, which had the highest proportion of neutral sentiment tweets. There were also 502 tweets denoting first-person product use or second-hand observation of another person’s use of smoking products. These reports also ranged by product type, with 40.8% for marijuana, 47.4% for tobacco, and 10.0% for vaping. Out of all tweets, 40.3% of those about marijuana indicated first-person use or second-hand observation, whereas this applied to 48.6% of tobacco-related tweets and 63.3% of vaping-related tweets. Across the top twenty colleges by tweet volume, first-person smoking product use or second-hand observation of another product user ranged from 31.8% from UC Berkeley to 73.7% for CSU San Jose . As the UC system and CSU Fullerton had smoke-free policies in 2015, and the remaining 22 schools in the CSU system did not have smoke-free policies, these tweets were assessed for evidence relating to campus policy violation.
Out of 486 tweets in 2015 indicating first-person smoking or second-hand observation of smoking, 146 were from schools with smoke-free policies. It should be noted that the content of these 146 tweets indicated smoking behavior on campus . As we captured 11 schools with smoke-free policies in 2015 and 19 schools without smoke-free policies , the number of these tweets per school was approximately the same among schools with smokefree policies and those without smokefree policies , potentially indicating a muted effect regarding the implementation of smoke-free policies, at that time, on these college campus populations and their compliance behaviors. Geospatial analysis revealed a distribution of tweets that approximately followed California’s population distribution, with a cluster in the San Francisco Bay Area and a cluster in Southern California, which was dominated by the Los Angeles Basin. However, comparatively fewer smoking-related tweets were captured from colleges in California’s Central Valley region. This distribution may have also been impacted by a low volume of tweets collected and sample bias for higher-population demographic areas based on the data collection process.Based on our use of tweets specifically geolocated for CA 4- year universities combined with a data filtering process to isolate tweets containing smoking-related keywords, 7,342 tweets were obtained for analysis that discussed smoking and also originated from California universities between 2015 and 2019. Within this corpus of social media messages, rates for use of the term “weed” decreased over time, changing from 28% in 2015 to 7% in 2019. Other commonly used smoking-related terms did not exhibit a percentage drop of this magnitude. The mechanisms underscoring the observed decrease in social media messages with this keyword are not clear but may result from evolving word choices to describe marijuana, decreased use of marijuana on CA college campuses, social inhibition of posting marijuana related public messages on Twitter, or some combination thereof. Further, it is unclear how passage of legalized adult-use cannabis Proposition 64 may have impacted these conversations, attitudes, and behaviors, particularly as despite state legalization, some college-aged students may not be of legal age and campus smoke free policies still restrict their use. Manual review uncovered 1,089 tweets explicitly related to smoking behavior and posted within the boundaries of California 4-year universities, with the majority of tweets expressing positive sentiment about smoking products and behavior. Five-hundredand-two of these tweets reported first-person use or secondhand observation of another person’s smoking behavior, with 146 tweets reporting possible violations of smoke- or tobaccofree campus policies that were clearly in place from 2015 but were also in the process of being fully implemented. These tweets indicate early lack of compliance to smoke-free campus policy implementation as self-reported by social media users. For campuses where policies were not in place, rolling benches tweets also reflect general positive sentiment about smoking and reports of smoking behavior, indicating possible barriers to enacting campus smokefree policies that would occur in 2017, when more smoke free campus policies across the California State University system were enacted.
These results provide early indications that smokefree campus policy implementation requires continued attention and sufficient resources to ensure appropriate health promotion, education on policy requirements, and policy enforcement measures in college communities. Overall, our analysis found a higher number of tweets in our corpus identified for tobacco and marijuana products, with comparatively fewer for vaping products geolocated for California university campuses. The majority of geolocated data collected during this study originated in 2015, which may explain the overemphasis on tobacco and marijuana Twitter conversations as vaping products were rising in popularity. Additionally, national debate about marijuana legalization occurred during this time frame, though was not legalized in California for adult recreational use until 2016 and licensure of cannabis retailers was permitted in 2018. As previously stated, national and state discussions relating to marijuana legalization may have influenced the relative social acceptability and volume of marijuana-related Twitter conversations among campus populations. Tweets about vaping had the highest proportion containing first-hand accounts of use or other persons engaged in product use and behavior. The increasing popularity of vaping products throughout the study time period, especially among the college aged population, may partly explain why college students posted about themselves or other people using vaping products in this context, despite having an overall lower volume than other smoking products . The increasing use of more discreet forms of vaping, particularly JUUL , may also have had an impact on social media engagement about vaping behavior, though more research is needed. Also, the associated health risks of vaping were relatively unknown during the study period, though the outbreak of EVALI in 2019 may have generated more attention and possible concern among users about potential health risks of vaping, though these conversations were not detected in this study . Importantly, most tweets that included conversations about tobacco products and behavior expressed positive sentiment. Though unclear from these preliminary results, the influence of “party culture” on college campuses, the opportunities to experiment and initiate with forms of substance abuse behavior, and the immediacy of pleasure from substance use may outweigh concerns, including those relating to long-term health risks, among college students in the United States as observed in this user sentiment . Interestingly, though marijuana tweets exhibited the highest proportion of positive tweets, they also exhibited the highest proportion of neutral tweets and the lowest proportion of tweets with negative sentiment. This finding may suggest relative homogeneity regarding marijuana attitudes, possibly as a consequence of debate regarding marijuana legalization during this time period. As the majority of all sentiment-containing tweets were positive, results from this study may suggest that outreach efforts to raise awareness about the health risks of tobacco and ATPs on college campuses may have limited resonance. However, these preliminary data also suggest discrepancies in sentiment between tobacco products, as well as differences in sentiment toward smoking across California universities. Therefore, policymakers and health promotion advocates should consider tailoring policy implementation and health communication for specific college students in California based upon evidence of latent receptivity toward anti-tobacco approaches and existing community sentiment toward smoking behaviors as detected in this study. Furthermore, future studies should more explicitly assess user reaction and sentiment to debate, communication and implementation of state-level policies that both legalize and restrict use of tobacco and smoking products, as well as how these macro policies interact with campus-specific smoke free policy perceptions for different tobacco, marijuana, and e-cigarette product categories. For example, actionable insights based on preliminary findings from this study indicate that users generally express more positive sentiment about tobacco use and smoking behavior. This may necessitate the use of campus-based health promotion and education activities that focus on reducing appeal of these products, such as restricting any form of marketing and promotion in or near campus communities. This should be coupled with broader state legislation to further restrict marketing and promotion that targets young adults and college communities. Further, perceived penalties for violating smoke- and tobacco-free campus policies may also impact compliance based on socioeconomic factors. For example, one user from UC Riverside tweeted, “other places might be more lenient, but UCs have a shitty tobacco and smoking policy and I got caught and now it’s over” [emphasis added to denote correction of misspelling]. Hence, data-driven approaches to assess receptivity and the impact enforcement has on smoking behavior should be built into smoke free program implementation iteratively. Importantly, the breakdown of smoking-related tweets between numerous college campuses as detected in this study presents challenges with respect to whether the distribution of tweet characteristics accurately reflects distributions in the underlying college populations. Nevertheless, similar work has been conducted which presents correlational evidence between characteristics of geospatially-specific social media posts and characteristics of populations in those areas . Furthermore, as over half of college students in California are between the ages of 18 and 24 , academic and demographic distributions of tobacco consumption within colleges may be the consequence of socioeconomic disparities in childhood and potential effects of these disparities on attitudes about smoking among parents, high schools, and/or neighborhoods that warrant further study .