December 27, 2020    Content analysis can extract valuable insights from texts, and the world is producing more texts than ever. However, the traditional method relies on humans reading and categorizing the content. That is too slow and expensive to be useful for most potential applications. This video explains the automated methods that reduce the time required from months to hours. Dr. Kyle Bahr and I have developed a computer program called the Social Licence and Controversy Detector and Analyzer (SLaCDA) based on the Natural Language Processing (NLP) approach to content analysis. The video explains how it works and shows how it can help find strategic insights from texts that previously would have taken too long to analyze.