Analyses of Google internet searches, reveal deep and otherwise elusive sentiments that are all too frequently unobserved by traditional research methods. Internet users often search topics they would be unwilling to ask their closest and most intimate confidants about. Thoughts about suicide, depression and the means one might use to take one’s own life are prominent examples – people may keep these thoughts very private but reveal them to google. Spring boarding from this central insight this paper seeks to determine whether suicide rates are higher in places where google searches about depression and suicide are common. Building on prior research, this project will assess the extent to which Google searches predict the 50-state suicide rate above and beyond traditional approaches. Using factor analysis three clusters of search terms were identified: suicide, depression, and gun-related. Suicidal and depressive search terms are found to be significantly associated with the suicide rate over the 11-year period (2006- 2016) even after controlling for divorce, unemployment, mental state, binge drinking, gun ownership, and yearly effects. These findings suggest that internet search data represent a, practical, and cost-effective method for studying suicide and other large-scale sociological phenomena. As fields such as public health, epidemiology, and psychiatry effectively incorporate internet and big data-driven methodologies, it is imperative that sociologists carefully consider its capabilities given its increasing utilization and potential.

Suicide and fatal drug overdose are a major public health and social problem in the US. Google search term data may help researchers understand variations in area-level suicide and fatal drug overdose rates. The extent to which an area Googles about suicide and drug-related topics may be indicative of the overall social environment in the area. This project tests if there is an association between suicidal Google searches and the suicide rate, and also tests if there is an association between drug-related Google searches and the drug overdose rate. This project tests these associations using two-way fixed effects linear regression to control for unmeasured confounding, while controlling for the major predictors of each outcome. The unit of analysis are Designated Market Areas (n=209) and the analyses observe a seven-year period (2010-2016) for a total of 1,463 unique observations. Results show that suicidal Google searches are associated with suicide rates, and drug-related Google searches are associated with overdose rates. These findings demonstrate that Google searches may provide researchers with an additional lens into the innermost thoughts, attitudes, and behaviors of individuals at an area level. These findings suggest that Google search data can assist in real-time suicide and drug overdose monitoring and prevention.