Authority under uncertainty in mediated information environments.
I study how people decide whose interpretations to rely on when information is unfolding, consequential, and mediated — whether it's mediated by platforms or AI systems.
My doctoral research examined severe weather livestreams as a high-stakes case of platform-mediated authority. Weatherfluencers interpret official data, narrate uncertainty, revise claims, compare sources, and respond to audiences in real time, while operating outside the credentialing and accountability structures that historically made weather expertise publicly legible.
The broader question is not simply whether people "trust" these creators. It is how publics make an interpretation usable when the interpreter's standing remains unsettled.
Severe weather livestreams are a high-stakes case of platform-mediated expertise. Audiences are not simply consuming content. They are watching a creator interpret official data, narrate uncertainty, revise claims, compare sources, and respond to audience input while the threat is still developing.
This setting makes the larger problem unusually visible: people may need to rely on an interpretation before expertise, accuracy, legitimacy, and accountability can be fully settled.
I call these creators weatherfluencers: platform-native creators who provide real-time severe weather interpretation for public audiences, often through livestreaming platforms such as YouTube.
Advised by Mark Zachry and David W. McDonald (co-chairs), with committee member Kate Starbird.
The dissertation contributes a vocabulary for understanding how authority becomes usable in platform-mediated environments where formal credentials and institutional accountability do not settle reliance.
Weatherfluencers operate outside the structures that traditionally authorize weather communication: NWS warning authority, broadcast affiliation, meteorological credentials, editorial oversight, emergency-management relationships, and formal accountability.
Creators make reasoning publicly visible as it unfolds through source triangulation, uncertainty narration, visual annotation, and on-screen revision. Audiences are not only consuming conclusions; they are watching the reasoning process become visible enough to inspect, question, corroborate, or provisionally rely on.
Audiences do not merely receive information. They help constitute the creator as a usable interpreter through repeated uptake, comparison, questioning, local reports, vouching, donations, moderation, and return across events.
Livestream chat participants do not merely react. They monitor, negotiate, and coordinate reliance in real time through questioning, corroboration, comparison, correction, and revision tracking.
The livestream becomes a site where audiences make unfolding conditions actionable even though the host's professional standing remains unsettled.
The weather case matters because it makes a broader problem visible. People increasingly encounter consequential interpretations through systems where authority is distributed across institutions, creators, platforms, audiences, algorithms, and AI.
The question is not only whether a source is trustworthy. The question is what makes an interpretation inspectable, accountable, and usable enough for reliance when people must act before certainty is possible.
My dissertation explains how publics evaluate interpretations when authority, accountability, and reasoning are only partially visible. That same problem now appears in AI-generated content, synthetic media, marketplace decision support, crisis communication, and platform governance.
As AI-generated content becomes part of product marketing, public information, crisis communication, and synthetic media environments, the question is not only whether people trust it. The question is what makes generated interpretation inspectable, accountable, and usable enough for reliance.
I am extending the weatherfluencer research into questions of authority, community, and recurrence in severe weather information systems.
The next phase of this work looks beyond single livestreams to how platform-native interpreters, audiences, local observers, and weather communities become part of a broader information ecology over time.
I am keeping the public description intentionally high-level while this work develops. The broader theoretical contribution travels to AI-generated content, synthetic media, marketplace decision support, and platform governance, but the empirical center remains severe weather information and the communities that organize around it.
Full publication list, talks, and media: Publications & Talks →