Is Artificial Intelligence the New Frontier for Research on Passion? On Inferring Passion from Text

Abstract

As the study of passion continues to grow in both relevance and interest, passion scholarship confronts new and sizeable challenges for (a) engaging in context-specific, theoretically-driven, inquiry into passion, and (b) identifying methods to collect sufficiently rich, longitudinal, data that can be paired with replicable, rigorous, data analytic approaches. In this paper, we aim to address these issues that hinder the advancement of the passion literature. We use Artificial Intelligence (AI) to infer entrepreneurial passion from multi-wave qualitative text data. By applying AI approaches (sentiment analysis and machine learning) to text data, we capture how different aspects of entrepreneurial passion change over time, and provide new insights into the changeable nature of passion in the specific context of social entrepreneurship. We hope that our work affords an ample foundation for future research—in passion and using AI—that are both theory-focused and practically useful.

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