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Demo Data from EDBT 2026 / reviewers in the wild / expert

Pemi Nguyen

dblp:290/8018 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

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

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis
misinformation analysis		 0.612022
Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlines · ACL (1) 2022

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

reasoning · 1.1frame semantics · 1.1
YearPublicationVenuePosition
2022 Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlines
abstract
Saadia Gabriel, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi, Yejin Choi. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2022.
Saadia Gabriel, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi, Yejin Choi 0001
 ACL (1)4