Affiliation:
1. University of Connecticut, Storrs, USA
Abstract
Multicultural individuals frequently feel they must check multiple boxes when responding to identity questions. In this investigation, we collected narratives from 402 bicultural individuals about their experiences with multicultural identities and used automated text-analytic tools to examine the valence of the narratives (sentiment analysis) and the most prevalent themes used (Meaning Extraction Method). In addition, we examined the relationships between the narratives and the two dimensions of Bicultural Identity Integration (BII) scales, Harmony and Blendedness. Findings suggested that the narratives were more emotionally positive than negative, and there were six most common themes. Furthermore, themes were significantly associated with BII scales. Our analyses provide deeper insights into the nature of bicultural identity using naturalistic language data.
Cited by
1 articles.
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