Crowdsourcing to Analyze Belief Systems Underlying Social Issues
- John Priniski, Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States
- Keith Holyoak, Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States
AbstractPeople’s beliefs and attitudes about social and scientific issues, such as capital punishment and climate change, appear to form complex but generally coherent networks. Understanding the nature of these networks is a prerequisite for designing interventions for changing beliefs on the basis of rational arguments and evidence. It is therefore important to develop methods to represent and analyze the form and nature of belief networks, which may not be explicitly verbalizable. Adopting an emerging approach that utilizes crowdsourcing to develop educational interventions, we mined discussions from the Reddit forum Change My View to determine which beliefs and types of information underlie people’s attitudes about capital punishment. By combining computational analyses based on a topic model with more qualitative assessments of the extracted topics, we found that moral arguments are more prevalent than statistical or data-based arguments. The present study serves as a test case for the open-sourced software crowdpy, a Python toolkit for running naturalistic studies on the web, which will enable other researchers to use crowdsourcing in their research. This approach sets the stage for research exploring potential interventions to change people’s beliefs.