Despite the importance of social networking sites on young adult alcohol use, few studies have examined Twitter as a conduit for sharing drinking behavior. However, this work generally uses random samples of tweets and thus cannot determine the extent to which Tweets correspond with self-reported drinking cognitions or behaviors. The primary aims of the present study were to (1) document basic patterns of alcohol-related Twitter activity in a subsample of young adult drinkers, and (2) examine whether willingness to drink, alcohol use, and negative consequences are associated with alcohol-related tweeting behavior.
Purpose
Despite the importance of social networking sites on young adult alcohol use, few studies have examined Twitter as a conduit for sharing drinking behavior. However, this work generally uses random samples of tweets and thus cannot determine the extent to which Tweets correspond with self-reported drinking cognitions or behaviors. The primary aims of the present study were to (1) document basic patterns of alcohol-related Twitter activity in a subsample of young adult drinkers, and (2) examine whether willingness to drink, alcohol use, and negative consequences are associated with alcohol-related tweeting behavior.
Methods
186 young adults age 18–20 completed an online survey and provided Twitter handle information. From these participants, a random sample of 5000 Tweets was coded by a trained team to determine whether tweets were related to alcohol use or not. Ordinary least squares regression analyses were conducted to determine whether the proportion of alcohol-related Tweets is associated with self-reported alcohol use willingness, behaviors, and negative consequences.
Results
Results indicated that not only are alcohol-related tweets common among young adults, but that the proportion of one’s overall tweets that are related to alcohol is significantly associated with willingness to drink, alcohol use, and negative consequences.
Conclusions
The results of this study are an important step to understanding how digital behavior (e.g., posting about alcohol on Twitter) is related to an individual’s self-reported drinking cognitions, alcohol use, and negative consequences and has implications for the way Twitter data can be used for public health surveillance and interventions.