Research

Analysis of 2.8M tweets tracing how patients collectively built the medical case for long COVID before institutional recognition, forming advocacy networks around knowledge-sharing.

Studies of r/maleinfertility and South Asian women-only Facebook groups revealing how moderators evolve into social activists and cross-posters function as boundary-spanning advocates.

How recommendation systems trap users in recursive loops around traumatic identity — and a design principle for routing users to empowering roles rather than curated suffering. Yet platform design profoundly mediated whether this helped or harmed: algorithmic recommendations pulled some users into misinformation loops, insufficient moderation obscured the line between experiential and evidence-based knowledge, and information overload produced learned helplessness where parents disengaged rather than finding the resources they needed about COVID uncertainty.

Crises vary in duration and form. Acute crises like COVID-19 and Hurricane Ida triggered real-time logistical coordination, locating scarce supplies, sharing resources among foster families, faster than formal institutions like the CDC. COVID discourse became increasingly polarized over time; earlier CDC statements were weaponized as receipts to counter new guidance, introducing data friction at critical flashpoints (e.g., new vaccine introduction). Extending this work internationally, a small set of interpretable Twitter topic features provides a strong signal explaining village-level wealth variation in Zambia, with poorer communities focused on immediate survival and wealthier ones on abstract policy.Zambian discourse itself shifted from ephemeral COVID concerns (lockdowns, testing) to durable infrastructure debates (energy plant construction, environmental effects).

GTFR-funded project extending crisis informatics to end-to-end encrypted platforms used by immigrant and lower-income communities in New Jersey. Working with Lazos America Unida, the project uses participatory action research to map how marginalized Latino communities share resources and authenticate information during crises, then moves into co-design workshops where community members build system requirements from their own situated knowledge upward.

How RedditCares, designed to flag users in distress, was systematically weaponized as a mass-flagging harassment vector against the populations it was meant to protect.

Analysis of 600K+ voice assistant commands from 456 older adults reveals relational and emotional use of Alexa — and the transparency failures that result when users treat AI as a confidant.

Naturalistic ChatGPT logs show how students develop “use genres” and how failure — when communicated transparently — cultivates critical AI competence rather than learned helplessness.

How opacity in AV systems normalizes data harvesting and how users construct inaccurate folk theories of system behavior when system communication is opaque — with real safety costs.

AI-Driven Navigation for Community Health — with Google & RWJ University Hospital — applying TID transparency requirements to clinical AI serving uninsured rural residents in NJ.

Analysis of Reddit discussions of Watchmen and Lovecraft Country showing how pseudonymity enables both anti-racist counterpublics and colorblind masked racism with deniability.

Two adaptive practices — pragmatic disengagement and interdependent navigation — reveal AI literacy as relational, culturally situated, and co-constructed across generations.

A South Korean cooperative mobility platform that invoked traditional mutual-aid values while admin-only logs and opaque algorithms prevented genuine community co-ownership.

Twitter topic features accounting for 60%+ of village-level wealth variation in Zambia; multimodal pipelines for aid allocation in Brazzaville, extended to NJ census tracts.

NLP analysis of nursing notes from a Rio de Janeiro hospital identifying linguistic indicators of racial bias and building fairness-aware algorithms for equitable clinical documentation.