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Alexandria Leto

dblp:371/2654 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2026
0009-0004-1261-8075ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Information extraction and text analysis · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › narrative understanding
narrative extraction
1.012026
A Structured Clustering Approach for Inducing Media Narratives · ACL (1) 2026
Natural language and speech › Information extraction and text analysis › text mining
text clustering
1.012026
A Structured Clustering Approach for Inducing Media Narratives · ACL (1) 2026
Natural language and speech › Information extraction and text analysis › discourse analysis
framing analysis
0.812024
Framing in the Presence of Supporting Data: A Case Study in U.S. Economic News · ACL (1) 2024

Methods — techniques the papers use, named apart from their topics

clustering · 1.0
YearPublicationVenuePosition
2026 A Structured Clustering Approach for Inducing Media Narratives
abstract
Rohan Das, Advait Deshmukh, Alexandria Leto, Zohar Naaman, I-Ta Lee, Maria Leonor Pacheco. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.
Rohan Das 0001, Advait Deshmukh, Alexandria Leto, Zohar Naaman, I-Ta Lee, Maria Leonor Pacheco
ACL (1)3
2026 Starting with DEI and Ethics - A New First-Year College Computer Science Introduction
abstract
Early exposure to ethical reasoning and diversity, equity, and inclusion (DEI) concepts is critical for preparing socially responsible computer scientists. To support this goal, we designed and implemented a required non-programming first-year undergraduate computer science course that is taken concurrently with an introductory programming course. This discussion-based course integrates DEI and ethics as foundational themes. The new course adopts a breadth-first structure delivered over a 10-week quarter, with 5 of the 18 sessions focused on DEI and ethics. Over three consecutive academic years, we collected pre- and post-course survey data from 451 students enrolled in the new course. Results show an %statistically significant increase in student's recognition of the importance of DEI and ethics and a substantial increase in understanding how these dimensions intersect with technical practice. In this experience report, we describe the course design, instructional methods, and survey instruments; present key findings; and reflect on lessons learned. This work contributes a model for embedding DEI and ethics into the early undergraduate computing curriculum.
Scott T. Leutenegger, Stephen Hutt, Andrew Hannum, Sanchari Das 0001, Alannah Oleson, Alexandria Leto, Sunny Shrestha
SIGCSE (1)6
2024 Framing in the Presence of Supporting Data: A Case Study in U.S. Economic News
abstract
Alexandria Leto, Elliot Pickens, Coen Needell, David Rothschild, Maria Leonor Pacheco. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024.
Alexandria Leto, Elliot Pickens, Coen D. Needell, David Rothschild, Maria Leonor Pacheco
ACL (1)1