Making information useful for people and AI.

I study how information should be represented to support human sensemaking at scale and how those representations should be adapted when both people and computational systems become users of them.

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On the 2026-27 academic job market · PhD Candidate, Syracuse University

Research program

01 / COMPUTATIONAL SOCIAL SCIENCE

Making large-scale discourse legible.

I develop computational methods for interpreting social meaning in large-scale text data.

TEXT MININGTOPIC MODELINGCOMPUTATIONAL NARRATIVES

FIRST-AUTHOR WORK4

UNDER REVIEW (targeting ICWSM 2027)From message similarity to communicative repertoires in coordinated political advertising

AACL-IJCNLP · 2026Beyond top words: MonoTM for topic modeling with interpretable monosemantic featuresARXIV ↗

ICWSM · 2026How growing toxicity manifests: A topic trajectory analysis of U.S. immigration discourse on social mediaDOI ↗

INFORMATION, COMMUNICATION & SOCIETY · 2025Climate communication in the stormy transition of Twitter to XDOI ↗

02 / HUMAN-CENTERED AI

When people and AI are both information users.

I study how AI systems represent information as memory and how that memory shapes their behavior.

AI AGENTSMEMORYPERSONALIZATION

FIRST-AUTHOR WORK3

UNDER REVIEW (targeting CHI 2027)Same personality setting, different assistance? Auditing personality controls in AI assistants

EACL · 2027 COMMITTEDMemory Availability Is Not Memory Use: Why Long-Term Dialogue Agents Need a Memory Use Policy

ASIS&T · 2026 FORTHCOMINGWhen AI memory fails: Reframing LLM agent memory as a knowledge organization problem

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Hi, I’m Una, a PhD candidate in Information Science and Technology at Syracuse University. My work spans computational social science and human-centered AI, with a shared interest in how computational systems represent and use information.

I’m currently on the 2026-27 academic job market. If you’d like to talk about research, collaboration, or opportunities, I’d be happy to hear from you.

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