of the substance list. Two of the co-authors manually reviewed a total of 2800 tweets: 1000 alcohol tweets, 500 drug tweets, 500 smoking tweets, 300 underage tweets, and 500 random tweets from the master dataset of all tweets. Inter-rater agreement was above 90% for all tweet subgroups. Manual labeling of these tweets yielded the following agreement rates between computer–generated labels and manually-generated labels: 88%, 86%, 75%, and 97% for alcohol, substance, smoking and underage tweets.

A list of 11 terms commonly associated with adolescents and young adults (hereafter refers as the “underage list”) was developed. For instance, "prom" is a term commonly associated with high school students. Another example is "homecoming dance," which is a dance commonly held at high schools and universities. Since the legal age for drinking(54%), and South Dakota (35%). Overall, the percent of happy tweets ranged from 27% to 48% for alcohol, 9% to 54% for smoking, and 7% to 35% for drug use. Additionally, the northeastern region of the United States had higher percentages of happy tweets relating to alcohol ( Fig 1 ). Maps displaying the national distribution of smoking and drug-related happy tweets are presented in S1 and S2 Figs.

The distribution of substance-related tweets is shown in Table 5 . Each entry denotes the proportion of tweets for the column (alcohol, smoking, drug) in a month. For instance, 20.1% of all alcohol-related tweets were captured in April. Of all alcohol, smoking, and drug-related tweets captured between April 2015 and March 2016, the largest proportion of tweets occurred in April.