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Recent years have seen a growing amount of research effort directed toward what positive psychologists refer to as self-transcendent or inspirational emotions, such as awe, admiration, elevation, gratitude, and hope. While these emotions are invaluable to promote greater human connectedness, an outward orientation, prosociality, and human flourishing, to date, researchers are not well-equipped to identify them either on mass media or private communication channels. Approaching from an interdisciplinary perspective, we aimed to construct a computational tool that can empower researchers to identify and analyze self-transcendent emotions among textual messages. To that end, we constructed and validated a dictionary tool that can be uploaded into the mainstream, textual analytic software (e.g., LIWC) to identify terms associated with transcendence-related emotional experiences as expressed in spoken and written languages. Potential applications for the newly developed tool and what it could mean for future studies of positive psychology are discussed.