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most citedTrump vs. Hillary Analyzing Viral Tweets during US Presidential Elections 2016

2 citations · 4 across the 6 of their papers we have counts for

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cs.CL20242 cited

NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task

Muhammad Abdul-Mageed, Amr Keleg, AbdelRahim Elmadany +5

We describe the findings of the fifth Nuanced Arabic Dialect Identification Shared Task (NADI 2024). NADI's objective is to help advance SoTA Arabic NLP by providing guidance, data…

cs.CL2024

Estimating the Level of Dialectness Predicts Interannotator Agreement in Multi-dialect Arabic Datasets

Amr Keleg, Walid Magdy, Sharon Goldwater

On annotating multi-dialect Arabic datasets, it is common to randomly assign the samples across a pool of native Arabic speakers. Recent analyses recommended routing dialectal samp…

cs.CL2023

ALDi: Quantifying the Arabic Level of Dialectness of Text

Amr Keleg, Sharon Goldwater, Walid Magdy

Transcribed speech and user-generated text in Arabic typically contain a mixture of Modern Standard Arabic (MSA), the standardized language taught in schools, and Dialectal Arabic…

cs.CL2023

Arabic Dialect Identification under Scrutiny: Limitations of Single-label Classification

Amr Keleg, Walid Magdy

Automatic Arabic Dialect Identification (ADI) of text has gained great popularity since it was introduced in the early 2010s. Multiple datasets were developed, and yearly shared ta…

cs.CL20231 cited

DLAMA: A Framework for Curating Culturally Diverse Facts for Probing the Knowledge of Pretrained Language Models

Amr Keleg, Walid Magdy

A few benchmarking datasets have been released to evaluate the factual knowledge of pretrained language models. These benchmarks (e.g., LAMA, and ParaRel) are mainly developed in E…

cs.CL2022

Don't Take it Personally: Analyzing Gender and Age Differences in Ratings of Online Humor

J. A. Meaney, Steven R. Wilson, Luis Chiruzzo +1

Computational humor detection systems rarely model the subjectivity of humor responses, or consider alternative reactions to humor - namely offense. We analyzed a large dataset of…