Proceedings of the Annual Meeting of the Cognitive Science Society

How we feel reflects a combination of recalled and recognized emotions. All existing self-report measures are basedsolely on recognized emotions. To understand the influence of recalled emotions, we developed a new method to recover humanemotional states based on emotional free association, in a task we call the emotional fluency. The present work investigated thedifferences between recall and recognition in human emotional states. We compared the emotional fluency task with self-reportmeasures, including PANAS, WEMWBS, and the Emotional Intelligence Scale. Using language statistics computed from theemotional fluency task, we developed multiple models for predicting self-report measures. We find that while recalled emotionscan predict recognized emotions, they highlight important problems with existing recognition measures, including emotionalcoverage and the difference between availability and accessibility. We also investigate the search process in emotional memory,supporting the role of unbiased memory sampling and higher emotional intelligence and mental well-being.