Mining Twitter and Google Searches is a More Efficient Method of Tracking Alcohol Use

A new study published in the American Journal of Preventative Medicine suggests that mining people’s alcohol-related tweets and online searchers is a faster, and more efficient method than the tradition method of collecting rigorous public health data through large survey-based studies.

“Online user-generated data are fluid and nimble – and have the potential to be really rich sources of information in specific geographic areas and during tight time intervals,” says Elissa Weitzman, ScD, MSc, of the Division of Adolescent/Young Adult Medicine and the Computational Health Informatics Program at Boston Children’s and the study’s first author and principal investigator in a press release. “We set out to draw a relationship between these novel data and established, curated, nationally representative survey data.”

In this study, researchers estimated search volumes for seven alcohol-related keywords (alcohol, alcoholic, alcoholism, drinking, beer, liquor, wine) relative to Google searches. They also estimated the number of Twitter posts broadcasting personal alcohol use, using natural language processing to classify tweets and eliminate any false positives.

Subsequently, the researchers compared these estimates to survey responses in the same state to questions about alcohol use, from the national Behavioral Risk Factor Surveillance System (BRFSS). The survey asked respondents, among its many questions: “During the past 30 days, how many days per week or per month did you have at least one drink of any alcoholic beverage such as beer, wine, a malt beverage, or liquor?”

According to the results of the study, 53% of respondents reported recent alcohol use. The researchers observed a notable link between a survey respondent’s use of alcohol and the relative volume of alcohol-related searches and tweets in that respondent’s state for the year and month they were surveyed.

“Informal social media and search data may be really important for detecting and responding to things that we don’t anticipate – or that occur naturally,” says senior author Lauren Wisk, PhD, formerly of Boston Children’s Hospital and now at the University of California Los Angeles.

Weitzman added that: “Our results give confidence in our public health tools and in using novel data approaches to measure health behaviors and policy effects — a real win.”