Casting a Wider Net: Using Automated Content Analysis to Discover New Ideas

Abstract

Psychology has made great strides in how researchers collect, analyze, and report data, but there has been less attention to improving hypothesis generation. Some researchers still rely on intuition, serendipitous observations, or a limited reading of the literature to come up with a single idea about a relationship between constructs. Although this approach has led to valuable insights, it can constrain thinking and often fails to generate a full picture of what is going on. New approaches, however, allow researchers to cast a wider net. Specifically, by reducing the cost and effort of examining a broader set of potential variables, automated content analysis (i.e., computer-assisted methods for extracting features from unstructured data) can uncover new insights and help develop new theories. We describe how these techniques can be applied to various research questions and outline methods and criteria that can be used to gain a wider perspective. In sum, automated content analysis is a powerful tool for identifying new and important phenomena, building (and sharpening) theory, and increasing impact.