Identifying #Addiction Concerns on Twitter during the Covid-19 Pandemic: A Text Mining Analysis

Background The 2019 Novel Coronavirus (COVID-19) is responsible for thousands of deaths and hospitalizations. To curb the spread this highly transmissible disease, governments enacted protective guidelines its citizens, including social distancing stay-at-home orders. These restrictions on interactions can be especially problematic individuals managing or recovering from addiction given that treatment often involves access to services resources became limited even unavailable at time. Social media sites like Twitter serve as a space users post questions concerns about timely topics allow researchers track common themes among public. goal study was identify how public discussing during COVID pandemic. Methods We performed text mining analysis analyze tweets contained “addiction” “covid” capture posts illustrated comments COVID-19 report 3,301 captured between January 31 April 23, 2020. conducted in United States, but multiple countries. Results most prevalent had do with offered by Acadia Healthcare Serenity Centers, attempts manage time while home, difficulties coping alcoholism amidst rising sales alcohol, attention ongoing health crises (e.g.,., opioids, vaping). Additional included affordable telehealth services, research France relationship nicotine COVID-19, gambling addiction, changing patterns substance misuse drug availability varies. Conclusions Analyzing content enables professionals public's Findings studies addressing preliminary analyses building more comprehensive models, which then used generate recommendations larger inform policy.