Comparing emotional diversity and emotional granularity in language

Le résumé fourni par la source

Natural language is a window onto how people see themselves and the world and make meaning of their circumstances. For this reason, psychologists have long used natural language to glean information about well- and ill-being. These inferences are often based on estimates of affective tone (“sentiment”), which represents overall positivity or negativity. Recently, there has been renewed interest in the specific role that emotion words may play in well-being. Assigning labels to feelings is thought to facilitate and/or reflect meaning-making that is clear and directed – scripts for what to expect, think, and do. Using a larger variety of emotion words suggests access to a wider range of scripts. The more specific emotion words are, and the better linked they are to surrounding context, the more precise scripts will be. These properties of emotion word use – variety and context-specificity – have been connected, respectively, to emotional diversity and emotional granularity, concepts associated with multiple aspects of well-being. It is unclear, however, whether these neighboring properties of emotion language relate to well-being independently, and whether they reveal insights that cannot be learned from affective tone alone. This study leverages state-of-the-art large language models to answer these questions.

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