Semantic Schema, Components, and Group Differences of Happiness and Unhappiness: An Investigation with a Word-association Network

Understanding everyday people's perceptions of the meaning of happiness is not only intrinsically interesting but also crucial for advancing academic research and informing policymaking on happiness and well-being. However, the question of how ordinary people conceptualize happiness—that is, the everyday conception of happiness—has rarely been systematically explored. This study applies a word-association network approach to examine the semantic schemas, components, and group differences in people's perceptions of both happiness and unhappiness. Specifically, we create a semantic representation of happiness and unhappiness from a survey using a mini-snowball word association task and then employ network analysis to identify semantic characteristics and demographic differences. Our findings suggest that the proposed method not only aligns well with previous studies' implications but also deepens our understanding of the structure by revealing new components of these concepts. Furthermore, the method facilitates further investigation of how semantic representations of happiness and unhappiness vary across demographic groups, highlighting both the general and semantic differences in their components. Overall, this study demonstrates the value of word-association networks for capturing everyday conceptions of happiness and unhappiness, offering both theoretical insights and practical implications for developing more accurate and culturally grounded measures.