Scott Alexander investigates the complexities of using Google Trends for mental health research, proposing methods to improve accuracy and interpretation of search data. Longer summary

Scott Alexander explores the challenges and nuances of using Google Trends for research, focusing on mental health-related searches. He demonstrates how individual keywords can be misleading and suggests averaging multiple related terms. Scott introduces a two-factor theory: one representing students' intellectual interest in mental health, which is declining, and another representing people with mental health issues, which is increasing. He discusses potential issues like temporal autocorrelation and provides tips for using Google Trends effectively, including the importance of considering school-related search patterns and the lack of need to adjust for general intellectual decline on the Internet. Shorter summary

Scott proposes adapting DW-Nominate, a political spectrum analysis tool, to study morality through real-life decisions, exploring its potential implications and limitations. Longer summary

Scott proposes using a method similar to DW-Nominate, a tool used to calculate politicians' positions on the political spectrum, to investigate morality. He suggests applying this method to real-life moral decisions people make, from major choices to everyday actions. The post explores how this could potentially group people into 'good' and 'bad' categories, identify the most moral actions, and possibly provide insights into contentious moral issues. Scott also discusses how this method might work in morally inverted societies like Nazi Germany, presenting three hypothetical outcomes and their implications for understanding morality objectively. Shorter summary