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Examines how hype shapes technology literacy on social media, suggesting new insights into collective knowledge creation.
The 2022 launch of ChatGPT triggered a wave of social media discussion about generative AI. Drawing on 215,279 posts from five months after this launch, we extend prior accounts of hype as a vehicle for strategic resource mobilization to develop a theory of hype as collective sensemaking and knowledge creation. Existing models rest on a fixed relational architecture: knowledgeable actors leverage information asymmetries to project visions, directing expectations top down. ChatGPT collapsed this architecture by making generative AI accessible, democratizing technology evaluation; meanwhile, social media emerged as the arena where relational publics could form, driving vision formation and contestation around generative AI from the bottom up, reshaping how a nascent technology acquired meaning. Combining grounded theory with computational text analysis, we develop a process model on the role of relational publics in hypes. We explain how collective knowledge accumulates through traceable conceptual prototyping, testing a technology’s capability and proposing meaning simultaneously, and how, when this knowledge crosses a technology literacy threshold, hype transitions from an expanding to a containing phase. The model advances our understanding of how novel technologies diffuse when crowds simultaneously co-construct visionary imaginaries and practical knowledge, and of the role social media plays in this process.
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Hamadi et al. (2026) studied this question.
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